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ADOPTION OF MICRO-INSURANCE: AN EMPIRICAL STUDY IN LUDHIANA CITY
Research Project Report
Submitted to the Punjab Agricultural University in partial fulfillment of the requirements for the degree of
MASTER OF BUSINESS ADMINISTRATION
in FINANCIAL MANAGEMENT
(Minor Subject: Economics)
By
Iqbal Singh (L-2010-BS-10-MBA)
Department of Business Management
College of Basic Sciences and Humanities
© PUNJAB AGRICULTURAL UNIVERSITY LUDHIANA - 141004
2012
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CERTIFICATE I
This is to certify that the research project report entitled, “Adoption of microinsurance: an empirical study in Ludhiana city” submitted for the degree of Master of Business Administration, in the subject of Financial Management (Minor subject: Economics) of the Punjab Agricultural University, Ludhiana, is a bonafide research work carried out by Iqbal singh (L-2010-BS-10-MBA) under my supervision and that no part of this research project report has been submitted for any other degree. The assistance and help received during the course of investigation have been fully acknowledged.
(Dr. Lalit Mohan Kathuria) Major Advisor Associate Professor Department of Business Management College of Basic Sciences and Humanities Punjab Agricultural University Ludhiana – 141004
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CERTIFICATE II
This is to certify that the project report entitled, “Adoption of micro-insurance: an empirical study in Ludhiana city” submitted by Iqbal Singh (L-2010-BS-10-MBA) to the Punjab Agricultural University, Ludhiana, in partial fulfillment of the requirements for the degree of Master of Business Administration, in the subject of Financial Management (Minor subject: Economics) has been approved by the external examiner along with internal examiner after an oral examination on the same.
_____________________ Internal Examiner
_____________________ External Examiner
_________________ (Dr. Sandeep Kapur) Head of the Department
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ACKNOWLEDGEMENT
The success of any project depends on the hard work and endeavour of not one but many, and this project is no exception. Acknowledging any one in mere words is a very difficult job. I would like to pay my sincere thanks to all those persons who helped me during this research project work with their able guidance and invaluable advice. It give me great pleasure in acknowledging the invaluable assistance extended to me by various personalities in the successful completion of this project report.. I express my heartfelt gratitude to my Major Advisor, Dr. Lalit Mohan Kathuria, Associate Professor, Department of Business Management, College of Basic Sciences and Humanities, for his dexterous guidance, inspiration, sustained encouragement, keen interest and precious time given to me during the course of research project and in successful completion of the manuscript. I express my deep appreciation to, Dr.Sukhpal Singh, Professor, Department of Economics and Sociology for his expert guidance. I owe my thanks to Dr. Sandeep Kapur, Professor-cum-Head, Department of Business Management and Dr. (Mrs.) Pratibha Goyal, Associate Professor, Department of Business Management for their valuable suggestions during the preparation of this manuscript. I express my sincere thanks to all other faculty members of Department of Business Management for providing necessary facilities during the tenure of my studies. Words at my command are inadequate to convey my sincere regards and respect to my loving parents and my family members for their deep affection, infinite encouragement and untiring moral support. Special thanks to my friends Varinder, Harsimran, Charu and Kanwarpal for their ever encouraging support, constant concern for my welfare and selfless sacrifices for my bright future.
Dated: Place: Ludhiana
__________________ (Iqbal Singh)
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Title of the Project Report study
:
Adoption of micro-insurance: an empirical in Ludhiana city
Name of the Student and Admission No. Major Subject Minor Subject Name and Designation of Major Advisor
:
Iqbal singh (L-2010-BS-10-MBA) Financial Management Economics Dr. Lalit Mohan Kathuria Associate Professor Department of Business Management Master of Business Administration 2012 51 + Annexure + Vita Punjab Agricultural University Ludhiana
: : :
Degree to be awarded Year of award of Degree Total pages in Project Report Name of University
: : : :
ABSTRACT India is a country with approximately 70 per cent of the population belonging to rural areas. The poor are more vulnerable to risks such as death, illness, injury and accident because of their economic circumstance. Approximately ninety percent are not covered by insurance. The present study was undertaken to find out the awareness regarding micro-insurance, analyze the factors influencing the willingness to adopt micro insurance and constraints in the adoption of micro insurance. To achieve these objectives, a sample, of 200 respondents was selected from Ludhiana city on the basis of convenience. The data were analyzed with statistical tools like mean score, Z-test, analysis of variance, and factor analysis. It was found that majority of the respondents were not aware about micro- insurance. Also, a small number of respondents had a micro-insurance policy. Life and health were most common forms of insurance undertaken by the respondents. The results highlighted that respondents consider ‘document and government support’, ‘income’, ‘trust and customer service’, ‘product awareness and availability’, ‘claim ratio’, and product flexibility’ as important factors influencing the adoption of micro-insurance. Respondents cited constraints like ‘trust on insurance companies’, ‘variable income’, ‘high cost ’, ‘awareness about the product’, ‘nonavailability of suitable product’, and ‘non flexibility of premium’ in the adoption of microinsurance product. Keywords: Micro-insurance, awareness, adoption, and constraints ______________________ Signature of Major Advisor ____________________ Signature of the Student
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CONTENTS
___________________________________________________________________________
Chapter
Topic
Page No.
_____________________________________________________________________
I. II. III. IV. V. INTRODUCTION REVIEW OF LITERATURE RESEARCH METHODOLGY RESULTS AND DISCUSSION SUMMARY REFERENCES ANNEXURES VITA 1-10 11-16 17-23 24-44 45-49 49-51
_____________________________________________________________________
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CHAPTER I INTRODUCTION Micro-insurance, the term used to refer to insurance to the low-income people, is different from insurance in general as it is a low value product (involving modest premium and benefit package) which requires different design and distribution strategies such as premium based on community risk rating (as opposed to individual risk rating), active involvement of an intermediate agency representing the target community and so forth. Insurance is fast emerging as an important strategy even for the low-income people engaged in wide variety of income generation activities, and who remain exposed to variety of risks mainly because of absence of cost-effective risk hedging instruments (Ahuja, 2005). India is a country of more than a billion people with more than 70 per cent of the population belonging to rural areas. In the past, government has attempted to provide various kinds of safety nets for the poor to cope up with unfortunate life events. However, the schemes or programmes are yet to cover a lot many poor. Insurance sector, where the total coverage is still 15 per cent as of now, in the life micro-insurance sector is estimated to have only at 2 per cent covering some 14 million adult lives. (Anonymous, 2010). Although the type of risks faced by the poor such as that of death, illness, injury and accident, are no different from those faced by others, they are more vulnerable to such risks because of their economic circumstance. In the context of health contingency, for example, a World Bank study reports that about one-fourth of hospitalized Indians fall below the poverty line as a result of their stay in hospitals (Ahuja, 2005). It was found that public ignorance is the widely rated as a significant barrier in the micro-insurance penetration. Very interestingly lack of probability of micro-insurance business is perceived not be a hindrance in the majority of the cases. Seventy seven countries out hundred were providing many efforts on availing access to insurance (Roth et al, 2007). Ninety per cent of the Indian population are not covered by insurance and signify an untapped market of nearly US $2 billion. This is a clear market failure, where the demand for microinsurance is not met by the supply of customized life and non-life insurance products. There is a clear role for the government here in linking micro-insurance to social protection schemes or exempting micro-insurance from the taxation applied to standard insurance products to encourage the provision of micro-insurance by commercial providers (Anonymous, 2007). The importance of insurance felt more when a poor family’s breadwinner dies, when a child in a disadvantaged household is hospitalized, or the home of a vulnerable family is destroyed by fire or natural disaster? Every serious illness, every accident and every natural disaster threatens the very existence of poor people and usually leads to deeper poverty. That’s where “micro-insurance” comes in (Anonymous, 2006). 1
1.1
History of Insurance sector in India The insurance sector has undergone many twists and turns over it’s 187 years of
operation, with a recent emphasis on growth and efficiency followed by an attempt to motivate rural and pro-poor focus. 1818 saw the advent of life insurance business in India with the establishment of the Oriental Life Insurance. General insurance business (nonlife) came into existence in 1850 with the commencement of the Triton Insurance Company. The first Insurance Act was formulated in the pre-independence period in 1938 (Anonymous,
2007). Regulated Indian insurers were divided into two core categories: life and general insurance. Life insurance includes products like endowment policies and retirement annuities. General insurance covers all other types of insurance. In 1956, the Indian Government nationalized the life insurance industry. The Government combined 154 insurance providers and formed the Life Insurance Corporation of India. The reasons given at the time were high levels of fraud in the industry and a desire to spread insurance more widely. General insurance remained in private hand until 1973 when it was nationalized (Anonymous, 2006). In 1999, the Insurance Regulatory and Development Authority (IRDA) was constituted as an autonomous body to regulate and develop the insurance industry. The IRDA was incorporated as a statutory body in April, 2000. The key objectives of the IRDA include promotion of competition so as to enhance customer satisfaction through increased consumer choice and lower premiums, while ensuring the financial security of the insurance market (Anonymous, 2012). The IRDA opened up the market in August 2000 with the invitation for application for registrations. Foreign companies were allowed ownership of up to 26 per cent. Today there are 24 general insurance companies including the ECGC and Agriculture Insurance Corporation of India and 23 life insurance companies operating in the country. The insurance sector is an already quite large and is growing at a speed of 15-20 per cent (Anonymous, 2012). 1.2 Meaning & Definition of Micro-insurance Micro-insurance is defined as “the protection of low-income people against specific perils in exchange for regular premium payments proportionate to the likelihood and cost of the risk involved”. Low-income people can use micro-insurance, where it is available, as one of several tools (specifically designed for this market in terms of premiums, terms, coverage, and delivery) to manage their risks” (Anonymous, 2006). Another definition highlights that micro-insurance is an insurance product that is targeted at low income households with a premium of less than Rs. 500 per annum and insured benefit of less than Rs 50,000 (Arvind, 2008). Micro-insurance has also been defined as an insurance that (i) operates by riskpooling (ii) financed through regular premiums and (iii) tailored to the poor who would otherwise not be able to take out insurance (Churchill , 2006 cited in Sahu, 2010). 2
Table 1 Type Of Cover (Rs) Life Insurance Health Insurance (Individual) Health Insurance (Family) Accident Benefit Table 2
Guideline for Life Insurers by IRDA Minimum Maximum Cover Cover 5000 5000 3000 30000 Min Term of cover 5 Years 1 Year Max Term of cover 15 Years 7 Years Min Age Entry 18 years Maximum Age Entry 60 Years
Insurer Discretion
10000 10000
30000 50000
1 Year 5 Years
7 Years 15 Years
Insurer Discretion 18 Years 60 Years
Source: Anonymous, 2008 Guidelines for Non Life Insurers by IRDA Min Cover 5000 Max Cover 3000 Minimum Term of cover 5 Years Maximum Term of cover 15 Years Min Age Entry 18 years Max Age Entry 60 Years
Type Of Cover (Rs) Livestock/Crop/ Asset Insurance Personal accident (per life/ earning member of Family
5000
30000
1 Year
7 Years
Insurer Discretion
Note: The minimum number of members comprising a group is at least twenty for group insurance. Source: Anonymous, 2008 At present, all insurance companies, both life and non-life in India are mandated by IRDA to do 20 per cent of their business from micro and rural insurance policies. In 2009-10, life insurers earned new business premium of Rs 4016.41 million from micro-insurance policies. Micro-insurance is not a profitable business segment for insurance companies because the premium generated is very low. For most insurance companies, distribution costs of micro-insurance products are often more than total premium earned ( Anonymous, 2012a). 1.3 Present Micro-insurance Scenario in India From a modest beginning, micro-insurance has been able to grow to a respectable size in the five-year period after issue of the IRDA Regulations. In the year 2010-11, the total premium collected under life and non-life micro-insurance portfolios put together was of the order of 15,430 million, out of which life insurance premium was 11,490 million and non-life insurance premium was 3,930 million (Anonymous, 2011). In 2010-11, 3.65 million microinsurance policies were sold in India in the year 2010-11 covering lives of 18.9 million people. The cumulative premium collected from micro-insurance was Rs.2.86 billion. Hence, micro-insurance constituted 4.59 per cent of the total lives covered, 7.6 per cent of total 3
number of policies and 0.23 per cent of premium collected by the insurance industry of India. With a premium collection of Rs.2.61 billion, the public insurer (LIC of India) is the market leader. (Mukerjee, 2012a). Table 3 Year 2007-08 2008-09 2009-10 2010-11 Source: Mukerjee, 2012 One third of the world’s poorest population are estimated to live in India. The World Bank estimates that 28 per cent of India’s population are living below the poverty line with more than 800 million people living in rural areas. In comparison with other countries, the micro-insurance market and distribution network in India are relatively well developed. In South America, Brazil appears to be the leading country with 56,00,000 insured persons and South Africa leads the African countries with 41,00,000 insured persons. Table 4 Country India Brazil South Africa China Indonesia Mexico Kenya Source: Coydon, 2011 1.4 Potential of Micro-insurance in Indian Context The potential market size for micro-insurance (life and non life) in India ranges between US $1,499 to 1,900 million approximately which is only expected to grow as microinsurance is better understood. In the case of life, the potential is estimated to be between US $350 to 500 million; in the case of non-life, between US $1,000 to 1,500 million approximately. The non-life estimation is limited to four types of coverage – (a) milch animals (b) livestock (c) health and (d) crop insurance. Some 52 percent of India’s population of 1.08 billion earns less than US $2 a day, of which one-third is estimated to earn less than US $1 a day. Micro-insurance can be an important constituent of a broader overall poverty Number of insured persons per country Insured persons per country 63,96,274 56,00,000 4,10,000 30,00,000 6,84,000 5,04,000 3,34,135 Number of micro-insurance policies sold for respective years Number of policies sold (in millions) 0.94 2.15 2.98 3.65
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reduction strategy to protect incomes and minimize loss of development gains among the low income populations (Anonymous, 2007). 1.5.1 Types of Micro-insurance Although there is no hard and fast rules describing the kinds of micro-insurance but according to prevalent micro-insurance products five categories could be made. With these five categories all the social and unadvantage group of people are tried to be covered (Anonymous, 2007). These are (a) Life micro-insurance (b) Health micro-insurance (c) Asset micro-insurance (d) Crop Insurance (e) Livestock or cattle Insurance 1.5.1 Micro-insurance schemes offered in India Following are the micro-insurance schemes offered by central government and public sector insurance companies in India. Janshree bima yojana This scheme was launched by the then Prime Minister Atal Bihari Vajpayee in 2000 as a group insurance scheme of LIC for the weaker sections of the society. The policy provides life, accidental and disability coverage to a group of people with minimum membership size of twenty five. This scheme provides benefits in the events of death (other than by accident) of the member, death/total permanent disability due to accident and permanent partial disability due to accident. It also provides the following coverage amount in case of Death of the member, an amount of Rs. 30,000, on death/total permanent disability due to accident, an amount of Rs. 75,000/?is payable. The premium under the scheme is Rs. 200/?per annum per member. Universal health insurance scheme is a community based insurance scheme was launched by the four public sector general insurance companies in July 2003. This scheme redesigned in 2004?05 made exclusively for persons and families below the poverty line with a premium of Rs. 165 for individuals, Rs. 248 for families of five persons and Rs. 330 for a family of seven. The benefits under the scheme were reimbursement of medical expenses up to Rs. 30000 towards hospitalization, an insurance cover for death due to accident to the amount of Rs. 25,000 and compensation due to loss of earning at the rate of Rs. 50 per day up to a maximum of 15 days. Varishtha Pension Yojana it is exclusively for unorganised sector workers of age 55 and above which is fully financed by the investment of the beneficiary with an annual return of 9 per cent in the form of monthly pension. The amount of pension benefit vary according to the amount invested from a minimum of Rs. 33,335 to a maximum of Rs. 2,66,665. The minimum and maximum monthly pension per month would be Rs. 250 and Rs. 2,000. The scheme is implemented by Life Insurance Corporation.
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Thrift fund scheme, “Under this scheme, every member is required to contribute 8 paise per rupee of wage earned and Central and State governments contribute 4 paise each to the fund”. The scheme is implemented by the Weavers Cooperative Societies/ Corporations. It provides temporary advance, partial and final withdrawal. New Insurance Scheme This scheme implemented by the United India Insurance Company and financed by the central government, state government and handloom weavers include payments in case of loss of dwelling due to natural calamities or fire, accidental death, reimbursement of hospitalisation charges and maternity benefits. Insurance for power loom weavers This scheme insures workers in the age group of 18 to 60 and with an income of Rs. 700 p.m. The central and the state government equally share the annual premium of Rs. 120. Benefits are given in case of natural death (Rs. 10,000) and accidental death (Rs. 20,000). In addition, the accumulated amount in the beneficiary’s running account earns an interest at 11 per cent per annum. National old age pension scheme It provides financial assistance of Rs 75 p.m. per beneficiary which has now been increased to Rs 200 p.m. to a destitute in the sense of having little or no regular means of subsistence from his/her own sources of income or through support of family members or other sources and whose age is more than 65. National family benefit scheme It targets households on the death of the primary breadwinner. The applicant should be of the age group of 18 to 65. A lump sum financial assistance of Rs. 10,000 is given. National maternity benefit scheme This is specifically targeted for pregnant women of 19 or more years belonging to households, upto first two live births. It gave a lump sum assistance of Rs. 500. The scheme was transferred to the Department of health and family welfare 19 with effect from 2000?01 from the Ministry of Rural Development. It has now been redesigned as Janani Suraksha Yojana in which cash benefits up to Rs. 1,300 in rural areas and Rs. 800 in urban areas to women in households for ante?natal care and institutional deliveries are provided. Jeevan Madhur It is a low premium endowment policy with accidental coverage. In this policy, if two full year premium has been paid, the cover will prevail for period of 2 years from the date of 1st unpaid premium. Minimum sum assured is Rs 5,000 while maximum is Rs 30,000. The age limit is from 18 years up to 60 years. Minimum premium is Rs 100 per month while maximum a person can pay is Rs 500 per month. Janata personal accident policy It covers any individual aged between 10 to 70. The sum insured is Rs.25, 000 to Rs.1,00,000 . Premium range is Rs.15 to Rs.240 per month risks covered accidents resulting in, death, permanent total disablement total and irrecoverable loss of use of limb loss of eye sight.
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Raj Rajeshwari Mahila Kalyan Yojna Policy this scheme provides economic security to women. All sections of women in the age group of 10 - 75 years irrespective of their income, vocation or occupation can be covered in this policy. Policy provides cover not only for the disablement of women but also for the death of her husband. Additional cover provides for temporary total disablement and also for loss damage to household goods. Benefits for Disablement of Insured women a) Permanent total disablement Rs.25,000 b) Loss of two limb/both eyes/one limb and one eye Rs.25,000 c) Loss of one limb/one eye Rs.12,500/. Premium is Rs15 per woman per annum or the basic cover and Rs.23 per woman per annum for both basic and additional cover (Anonymous 2010). Jeevan Mangal is a term assurance plan with return of premiums on maturity, where the premiums are required to be paid at regular intervals over the term of the policy. Persons 25 above the age of 18 years and upto the age of 60 years can participate in the scheme. The maximum maturity age is at 70 years. The term of the policy is 10 to 15 years with regular premium, however it is only 10 years for single premium. Also, the minimum and maximum sum assured are Rs. 10,000 and Rs. 50,000 respectively Following are some schemes offered by private sector insurance companies: Tata AIG’s Ayushman Yojana is a single premium plan where the policyholder pays the premium at the beginning of the policy term and gets the dual benefit of living as well as risk of death. This can be especially useful for those rural people who have a seasonal income. The policy is for the rural people falling in the age group of 18?60 years. The term of the policy is 10 years. AVIVA’s Jana Suraksha provides comprehensive financial protection to the children/dependants of the policy holder through low cost life insurance and guaranteed lump sum amount in case of death of the policyholder during the term of the policy. The term of the policy is for 5 or 10 years, subject to the maximum maturity age of 50 or 55 years respectively. The policyholders of age 18?45 years can participate in this and are required to pay the premium till the policy terms. The minimum life cover is Rs. 20,000 and the maximum is Rs 50,000. In the event of the death of the policyholder, the total sum assured is paid to the nominee. In case if the death occurred due to an accident, the life cover becomes the double. The maximum maturity age is 55 years. AVIVA’s Amar Suraksha is a protection plan that helps to secure the family’s future through a guaranteed lump sum amount in case of the death of the policyholder and with an option of minimum annual premium of Rs. 500. The term of the policy varies from 5 to 20 years with maximum maturity age at 50 years. The persons of age 18?45 years are eligible for thescheme. The premium paying term is same as policy term with minimum sum assured at Rs.20,000 and maximum at Rs 1,00,000. It covers both the living and death benefits. In case
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of death, the sum assured is paid to the nominee, while in case of maturity, the total premium paid is refunded back to the policyholder Birla sun life’s Bima Suraksha Super It provides life insurance cover on the payment of regular premium. The nominee gets the sum assured in the unfortunate event of death. This plan is simple and convenient with no medical tests and minimum documentation. A person aged 18 years can enter into the contract but the maximum entry age varies according to the term of the policy. Tata AIG’s Navkalyan Yojana Is a regular premium payment, low cost term plan for the rural adults who seek life insurance protection without any maturity benefit. It is five years term plan with age restrictions of 18 to 60 years AVIVA’s Grameen suraksha It is a term Insurance policy with total premium paid back on maturity. In this policy, only two yearly premiums are to be paid. This policy covers people up to the age of 55 Years only. This acts as a barrier in this policy (Anonymous 2012c). Insurance companies in India The number of insurance companies stood at 48 at the end of 2010-11, consisting of 23 life insurers, 24 non-life insurers and a reinsurer. Edelweiss Tokio Life Insurance Company was granted registration in the year 2011-12, leading to total number of insurance companies increasing to 49 as at end-September 2011. The Indian Insurance sector can basically be divided into two parts, one which is offering life insurance product others which include the rest. Then the sub categories could be formed in the form of public and private insurers. Public sector is still the dominant one when it comes to microinsurance specially offering the micro-insurance products to individuals. The only player in the life insurance category of public sector is still the LIC while the non life insurance sector now comprised of five companies. These are, National Insurance Company, New India Assurance Company, Oriental Insurance company, United Insurance Company, Agriculture Insurance Company. In total there are 20 insurers providing insurance in private sector 8 of them are non life insurers and 12 are life insurers. Birla Sun Insurance Company, HDFC standard life insurance company, ICICI prudential Life Insurance Company, Max New York Life insurance company, SBI life Insurance Company, TATA AIG life insurance company, AVIA life insurance company. 1.6. Classification of micro-insurance products India is home to many experiments in micro-insurance. Though officially there are 23 registered micro-insurance products filed by 15 insurance companies, there are a host of registered and non registered micro-insurance products in India. Micro-insurance products in India can be classified into four different types (Mukherjee, 2012). 8
Classification of Micro-insurance in India ? ? Products registered as micro-insurance products Rural and social products not registered as micro-insurance products Community based products in partnership with insurance companies; Independent community based micro-insurance products. Challenges in the way of Micro-insurance Although the micro-insurance has came a long since the micro-insurance regulations 2005 but the way for the micro-insurance has not been easy it has confronted many challenges in its way. The following issues play the key role of influencing the growth of the microinsurance industry in India, and coming as a hinder in the micro-insurance industry (Anonymous, 2012b).: 1. Difficulty in distribution is one of the most cited reasons for absence of rural insurance. The high costs of penetrating rural markets, combined with underutilization of available distribution channels, hinder the growth of rural insurance services. This adds to costs, both, managerial and financial. Like inclusive credit, inclusive insurance is expected to be a “low ticket” business, requiring volumes for viability. 2. Pricing, including willingness to pay and the availability of subsidies, influence the market. In the absence of a historical data base on claims, premium calculations are based on remote macro aggregates and overcautious margins. Building and sharing claims histories can help in aligning pricing decisions with actuarial calculations, thereby reducing prices. 3. Product design There is a mismatch between needs and standard products on offer. 4. Poor customization of product there is a low demand for what is available and insurance product developed. 5. The lack of insurance awareness is also seen as a challenge and translates into a relatively low demand for micro-insurance services. Commercial insurance companies, directly and through their partners, need to engage in the provision of insurance education. 6. Smaller premium is also a challenge since the amount of collected premium usually gets more than the marketing expenditure, acquisition cost of respondents as they are often living in remote areas and amount returned as claim. All these things add to high cost ratio for the companies. 7. There are specific reasons for low demand for insurance in spite of intense need. Suppliers have their own concerns which help to explain why there have been so little
?
? 1.7
9
efforts at market development. Consequently, the rural market is characterized by limited and inappropriate services, inadequate information and capacity gaps. 8. Cumbersome and inappropriate procedures inhibit the development of this sector. 9. The survey respondents state that the lack of available data, which is needed for risk assessment and premium calculations, is another significant challenge when entering this market. (Anonymous, 2012b). 1.8 Need for the present study India is the country currently having the most dynamic micro-insurance sector in the world. Liberalization of the economy and the insurance sector has created new opportunities for insurance to reach the vast majority of the poor, including those working in the informal sector. Even so, market penetration is largely driven by supply, not demand. Micro-insurance in India has valuable lessons for rest of the world, particularly in the regulation of the industry (Anonymous, 2006). Although the type of risks faced by the poor such as that of death, illness, injury and accident, are no different from those faced by others, they are more vulnerable to such risks because of their economic circumstance (Ahuja and Khasnobis, 2005). Microinsurance is specifically designed for the protection of low-income people, with affordable insurance products to help them cope with and recover from common risks. It is a market-based mechanism that promises to support sustainable livelihoods by empowering people to adapt and withstand stress (Anonymous, 2006) In the context of health contingency, for example, a World Bank study (Peters et al 2002), reports that 25 per cent hospitalized Indians fall below the poverty line as a result of their stay in hospitals. The same study reports that more than 40 per cent of hospitalized patients take loans or sell assets to pay for hospitalization (Ahuja and Khasnobis, 2005). There are some 14 million adults are covered by life micro-insurance in India. In a country with some 120 million families living on less than $2 a day, this is a very small proportion of the potential micro-insurance market and an indication of an untapped market of nearly US $2 billion. There is a need to understand the insurance requirements of low-income group, to study the awareness about micro-insurance, identify the factors affecting the willingness to adopt micro-insurance and identify the constraints in the adoption of micro-insurance.
So, the present study was aimed to achieve the following specific objectives: 1 To analyze the perception of respondents toward willingness to adopt microinsurance 2 To examine the constraints in the adoption of micro-insurance 10
CHAPTER II REVIEW OF LITERATURE An attempt has been made to present, in brief, a review of selected studies, which have a: direct or indirect relevance to this study. This is likely to provide a glimpse of work done on micro insurance. Aliber and Ido (2002) found that there was enormous scope for increasing the practice of microfinance institution based micro insurance, not just in terms of overall volume of business, but also in the variety of risks covered. Microfinance institutions can provide financial services, which provide insurance-like benefits. The regulatory framework needs amendment to accommodate micro insurance and there is a need for sensitization and education of prospective micro insurance claimants. Srinivasan and Arunachalam (2002) examined the demand for insurance from micro small enterprises and identified the details of microfinance institution activities concerning the (practical) operations for the provision of insurance services and also isolated difficulties they face. Ahuja and Jutting (2004) concluded a study based on community based micro insurance schemes and analyzes the how institutional rigidities that affect the demand for health insurance among the poor? Using a simple analytical model, the paper demonstrates that lack of demand for insurance need not necessarily be the result of affordability. Institutional rigidities, such as credit or borrowing constraints, may prevent low-income households from demanding insurance that they can otherwise afford. The paper also found that the absence of insurance can increase a poor household’s vulnerability, and push them into a poverty trap. For the poorest of the poor, affordability of insurance was still a major issue. Finally given these findings, the paper argued that the appropriate public intervention to generate demand for insurance may not be to subsidize premiums. Instead, the paper recommended that public intervention should remove institutional rigidities, for example, in labour, credit and product markets. Abels (2005) attempted to provide insights on the issues related to micro insurance and how micro insurance can be used to reduce the risk exposure of the low-income population. The note also provides a detailed analysis of the sector from the perspectives of clients, providers and supporting roles. Ahuja and Khasnobis (2005) observed that prospects of micro-insurance in India, and suggested strategies for its further extension. Analyzing the early evidence on micro 11
insurance, the paper also highlighted the current initiatives being contemplated to strengthen micro-insurance activity in the country. The authors study the developments on the supply side of micro insurance and observed that of the 80 listed insurance products, 45 cover only a single risk. Private insurance companies have more products than public companies. The available products cover a wide range of risks and most of the health insurance products exclude pregnancy related illness etc. The authors assessed the developments on the demand side of micro insurance and observed that 51 schemes are listed, with almost all being in the nascent stages. Nearly all insurance schemes are linked with micro financial services. Life and health are two most popular risks for which insurance is demanded. Barbin et al (2005) indicated that microfinance institutions have unique capabilities to cost-effectively delivery micro insurance to the informal sector. Micro insurance complements the microfinance institutions’ other interventions with medium scale enterprises because it reduces their vulnerability to business and personal risks. Just as microfinance has gained widespread acceptance as an effective development strategy; micro insurance, too, promises to be a sustainable approach to risk management for the informal sector. Microfinance institutions are currently in the best position to provide micro insurance to the informal sector and should actively experiment and innovate to make the mainstreaming of micro insurance a reality. Paul (2006) discussed the attempts to provide insurance against risks afflicting the poorest. It presents empirical evidence on the impact of different types of micro-insurance, and recommended the idea of ‘quasi-insurance’—the provision of insurance functions through a non-insurance route. The paper argues that micro-Insurance so far has been somewhat supply-driven rather than driven by effective demand, especially from the poorest, and thus the insurance products which would benefit the poorest are still at a limited stage of development. Institutional innovations and new insurance products therefore deserve promotion. Ramesh (2006) revealed health insurance schemes are increasingly recognised as preferable mechanisms to finance health care provision. In this direction micro health insurance schemes and community based health insurance schemes are assuming
significant importance in reaching large number of people. However, at the community level despite low premiums the penetration of health insurance is small. First determine the factors which affect the insurance purchase decisions. The results indicated that income and healthcare expenditure are significant determinants of health insurance purchase. Age, coverage of illnesses and knowledge about insurance were also found to be affecting health insurance purchase decision positively. For the decision regarding amount of health 12
insurance purchase, income was found to be having significant but non-linear relationship. In addition, number of children in the family, age, and perception regarding future healthcare expenditure were also found to be significant. Roth et al (2007) discussed the landscape of micro-insurance in the world’s poorest countries and found that public ignorance was the widely rated significant barrier in the highest public score in Togo, Burkina, Demonic Republic and Panama. 77 countries out of 100 countries under study were providing many efforts on availing access to insurance. Arvind and Renukumar (2008) observed that households (both microfinance institution clients and non-microfinance institution clients) had an access to and had taken regular insurance policies through the insurance agency network. Their associations with microfinance institutions showed well in their understanding and need for insurance. It was found that there was a strong need for endowment policies which the current micro insurance programmes fail to offer. At the microfinance institution level, though they understand the client needs well, they were not in a good position to carve out a suitable product for their clients. Insurance companies understand the basic issues in expanding into the rural sector like the necessity to associate with a trusted institution. But companies were still reluctant to design a suitable and an affordable group product that requires working closely with micro finance institutions and clients. Thus the study revealed the requirement for more education about micro Insurance at the mass level, the necessity for more bargaining power and insurance training at the microfinance institutions level and the need for a social perspective at the insurance company’s level. Dercon (2008) presented a selective overview of the current state of research on microinsurance. Its key purpose is to identify knowledge gaps that deserve further investigation. The study discussed the three core issues: the need for careful evaluation of the impact of microinsurance on the poor, the need to increase our understanding of the nature of the demand for microinsurance, including dimensions related to trust and the understanding of insurance by the poor, and finally, the need for further research on supply dimensions, focusing on the key challenges and bottlenecks for widespread and sustainable provision of microinsurance. Thankom and Susan (2008) analyzed the role of micro-insurance as an element of social protection. It outlined the current status of micro-insurance provision in Ghana and SriLanka, two countries with very different socio-cultural backgrounds. It concluded that both countries are unlikely to extend their social security systems to the entire population in the
13
short to medium term, making private micro-insurance initiatives essential mechanisms to help people reduce their vulnerability. Brau et al (2009) analyzed that micro insurance institutions and instruments have developed rapidly over the last decade, with policies covering tens of millions in the base of the economic pyramid for markets in Africa, Asia, and Latin America. Ranging from simple policies providing life or health insurance to complex policies covering catastrophic risks for small landholders, it is a market with proven potential which demands closer attention. Cai et al (2010) observed the formal micro insurance in effect of economic development? the study results from a large randomized natural held experiment conducted in south-western China in the context of insurance for sows. The study found that providing access to formal insurance significantly increases farmers' tendency to raise sows and farmers are not previously efficiently insured through informal mechanisms. The study provided evidence to trust, or lack thereof, for government-sponsored insurance products was a significant barrier for farmers' willingness to participate in the formal insurance program, despite partial premium subsidy from the government. Hongbin et al (2009) revealed results from a large randomized natural field experiment conducted in south-western China in the context of insurance. The study assured two important questions about microinsurance. First, how does access to formal insurance affect farmers' production decisions? Second, what explains the low take up rate of formal insurance, despite substantial premium subsidy from the government? The study found that providing access to formal insurance significantly increased farmers' tendency to raise sows. We also provide several pieces of evidence suggesting that trust, or lack thereof, for government-sponsored insurance products is a significant barrier for farmers' willingness to participate in the insurance program. Mosley (2009) presented empirical evidence on the impact of different types of micro insurance, and recommends the idea of ‘quasi-insurance’—the provision of insurance functions through a non-insurance route—where institutional or regulatory constraints prevent insurance proper from being offered. The paper argues that micro insurance so far has been somewhat supply-driven rather than driven by effective demand, especially from the poorest, and thus the insurance products which would benefit the poorest are still at a limited stage of development. Institutional innovations and new insurance products therefore deserve promotion. Leatherman (2010) revealed the emergence of health microinsurance programmes worldwide provided hope to the poor. This study includes a literature review of 68 documents 14
covering the period from 1999 to 2010 and expert interviews with more than 31 experts representing 25 organizations. It focuses on private sector and discussed the challenges that limit the growth and impact. In addition to identifying barriers to success, the authors presented innovations that may move the field forward, including collaboration with public programmes. Matul (2010) fount that over 14 million low-income people in Africa who were covered by microinsurance at the end of 2008, almost double where this figure stood in 2004. Even with such growth, substantial parts of the continent remain almost barren of microinsurance. The paper concluded with a discussion of micro insurance challenges that must be overcome in order to facilitate broader, high-quality expansion in the years to come. Sahu (2010) examined micro-insurance programme in select areas and found that that the existing micro-insurance products were not demand driven in both high and low outreach areas. There was lack of understanding, awareness, extension services and development of insurance market that grossly affect wider use of insurance products and its uptake, particularly, among low-income sections of the society. Akotey and Gemegah (2011) revealed demand for micro- insurance in Ghana has found that premium flexibility, income level and nodal agency were significant determinants of micro-insurance demand. Insurance knowledge, expectation (trust) and marital status were also found to have positive and significant impact on the demand for micro insurance. Interestingly, the empirical analysis highlighted that formal education is not a significant determinant; rather one’s level of insurance knowledge had a positive and significant impact on micro-insurance demand. Bendig and Arun (2011) presented evidence on the determinants of insurance participation using probit models on household survey data from Sri Lanka, conditional on household’s microfinance institution enrolment. Further, the study employs multivariate probit regressions to analyze factors affecting the participation in different types of insurance. It was found that the household’s experience of a family related shock is positively associated with the participation in micro health insurance schemes under study. There was strong evidence that micro insurance has not yet succeeded in proportionately reaching the most vulnerable households. Notably, education of the household head was found to be a strong determinant of micro insurance participation. Heenkenda (2011) examined farmers’ willingness to pay for an Index Based Micro Insurance Scheme for paddy crops to protect against production loss caused by natural disasters in Sri Lanka and to assess product preferences for this IBMS. The contingent valuation 15
method was used to elicit the willingness to pay for the hypothetical IBMS. For product preferences, a conjoint analysis was conducted to study their relative importance and to discover the relationships between different attributes and the characteristics of the respondents. The results revealed that the interest in joining IBMS is 88 per cent overall. When willingness to pay is assessed, it is found that most potential purchasers would prefer a higher level than that offered by the existing conventional insurance plan. The results of the preference analyses demonstrated that for IBMS products can be adapted for specific locations in order to maintain demand. Matul et al (2011) presented results from the analysis of 15 micro-insurance schemes in Kenya, India and the Philippines using the international labour organisation's client value assessment tool called PACE (Product, Access, Cost and Experience). The PACE tool looked at the added value for clients from insurance products by comparing them to each other and to alternative means of offering protection from similar risks. The results presented that there is a place for micro-insurance to add value on the top of informal risk-sharing practices and existing social security schemes to protect low-income populations against life and health risks. The paper presented also a menu of interventions that can further improve client value from micro-insurance. Thankom A (2011) found that micro insurance was an emerging concept protecting households from the potentially catastrophic expenditures associated with family related shocks. The study presented evidence on the determinants of insurance participation using probit models on household survey data from Sri Lanka, conditional on household’s microfinance institution enrolment. Further, we employ multivariate probit regressions to analyse factors affecting the participation in different types of insurance. We find that the household’s experience of a family related shock is positively associated with the participation in micro health insurance schemes under study. There is strong evidence that micro insurance has not yet succeeded in proportionately reaching the most vulnerable households. Notably, education of the household head is a strong determinant of micro insurance participation. Roy and Holtz (2011) revealed health micro insurance schemes require that patients pay cash at the time of receiving health care services, and then seek reimbursement from the insurer at a later date. For low-income households, this could be a severe financial barrier. One common way to alleviate this barrier was to set up a third-party payment mechanism with selected health care providers. A third-party payment mechanism is a model for claims payment in which insured patients are not required to pay the entire cost of health services covered by the health micro-insurance scheme at the time the services are rendered. This 16
study on the experience of various health micro-insurance schemes and presented the pros and cons of using a third-party payment mechanism. Rusconi (2012) revealed products offered by Indian insurers that combine the benefits of insurance and saving. Combining these two financial instruments made sense when considering the complex financial lives of low income households. The study presented a framework that can be used to analyse the design of savings linked insurance products. The analysis highlighted the different approaches taken by the insurers, and provides preliminary insights for others interested in designing similar products. The review of above literature indicates that though few studies have been done conducted to check the awareness, and factors inducing low income people to purchase micro-insurance product, but there seems to be a lack of study analyzing the factors affecting the willingness to adopt micro-insurance and constraints in the adoption of micro-insurance. The present study is therefore an effort to fill the gap and to further the work already done in this field.
17
CHAPTER III
RESEARCH METHODOLOGY
It is imperative to decide upon the research methodology well in advance to carry out the research in a most effective and systematic way. This chapter describes the research methodology adopted to serve the objectives of the study in an effective manner. This chapter consists of the five sections namely ‘conceptual framework’, ‘population and sample selection’, ‘collection of data’, ‘analysis of data’ and ‘limitations of the study’. These sections have been discussed below. 3.1 Conceptual framework The present study aims to examine the awareness of respondents towards insurance, micro insurance, micro-insurance schemes, to identify the various factors effecting the willingness to adopt micro-insurance. Also perception of respondents belonging to different income groups regarding constraints faced in the adoption of micro-insurance. For achieving the objectives primary data were used and the secondary information was also studied to find the relevant literature and statistics regarding micro insurance products and schemes run by government for the disadvantageous groups of India. For this study, respondents engaged in services as well as self-employed were selected for survey. Population for the study consisted of respondents of Ludhiana city. 3.2 Population and sample selection
The population of the study comprised respondents from both informal sector and formal sector. Formal sector mainly consisted of respondents providing services while informal sector mainly compromised of self employed. Individuals belonging to low income group comprised the major proportion of the sample; A sample of 200 respondents was selected on convenience basis and willingness of respondents to share information. 3.3 Collection of data To meet the objectives of the study primary data were collected through a predesigned, structured and non-disguised questionnaire. Before designing the questionnaire, a desk research was conducted to study the literature available on the subject. Various studies were reviewed to have a thorough understanding about various parameters to be included in questionnaire and accordingly a self-administered and structured questionnaire (as given in the Appendix) was designed to collect information from the respondents. Questions were specifically designed to get in-depth information about the profile of the respondents, awareness level of respondents towards insurance, kinds of insurance products, micro-insurance, and various micro-insurance schemes constraints faced in the adoption of micro-insurance. Questions related to factors influencing willingness to adopt 18
were also included. Both open ended as well as close ended questions were asked. Respondents were also asked scale based questions. For scale based questions, respondents were asked to provide their responses on a five-point Likert scale indicating their level of agreement, where ‘5’ showed ‘extremely important’, ‘4’ as ‘very important’, ‘3’ as ‘important’, ‘2’ as ‘less important’ and ‘1’ as ‘not at all important.’ The questionnaire was pre-tested and suitable modifications were incorporated before the final selection of the text of the questionnaire. Before filling the questionnaire, main objectives of the research were explained to the respondents. 3.4 Analysis of data The data collected through the questionnaire were converted to a master table which facilitated tabulation of data in desired form. The collected data were then grouped into tables and analyzed using various statistical tools like frequency distribution, percentage, mean score, standard deviation, Z-test, ?2 -test and factor analysis. To study the level of awareness among respondents, various questions regarding insurance, micro-insurance and various micro-insurance schemes were asked. A score of 1 was assigned to each question. Based on the scores, awareness level of respondents was grouped into 2 categories i.e. aware and not aware. Mean score was calculated for those questions, where respondents were asked to provide their responses on a 5-point Likert scale. The respondents were asked to indicate level of importance towards willingness to adopt micro-insurance and constraints faced in the adoption of micro-insurance. The weights given were as follows: 5 – Extremely Important 4 – Very important 3 - Important 2 – Less Important 1 – Not at all Important Mean score was calculated using the formula: Mean Score = (? Wi * Fn) / n i = 1 to 5 where Wi = weight attached Fn= associated frequency n = number of respondents If the mean score was more than mid point of the scale i.e. 3, it was concluded that respondents by and large tend to agree with the statement. Obtained mean score was tested against assumed mean of 3. For this, Z-test was applied and Z value was calculated to find out the statistical significance of each factor. The 19
formula used to calculate the z values is given below: Z=
( X ? µ) n S
X = calculated mean of the sample µ = assumed mean of the population i.e. 3 n = sample size S = standard deviation of the sample S=
?( X ? X ) 2 n ?1
Chi-square test (?2) was applied to test the statistical significance of the observed association between rows and columns of contingency tables. Chi-square was calculated by using the formula: ?2 = ? [(O-E)2 / E] Where O = Observed frequencies E = Expected frequencies And E = nr nc / n nr = total number in the row nc = total number in the column n = sample size Anova - one way an analysis of variance is a procedure used for comparing sample means to see if there is sufficient evidence to infer that the means of the corresponding populations distributions also differ. Analysis of variance is able to compare data for two or more distributions (George and Mallery, 2009). The analysis provided a test of the hypothesis that each sample is drawn from the same population against the alternative hypothesis that population is not the same for all samples. One-way classification was used. ANOVA was calculated using the following formula: Table 5 ANOVA Table : One-way classification model Sum of squares SSC SSE SST Degrees of freedom c-1 n-c n-1 Mean square Variance ratio of F MSC/MSE
Source of variation
Between samples Within samples Total
MSC=SSC/(c-1) MSE-SSE/(n-c)
20
Where, SST = Total sum of squares of variations SSC = Sum of squares between samples (columns) SSE = Sum of squares within samples (Rows) MSC = Mean sum of squares between samples MSE = Mean sum of squares within samples n = Total number of items c = Total number of columns Value of F was calculated at 5% level of significance The sum of squares total (SST) can be calculated as SS = ?X2 - CF where, CF =
??X ?2
N
and N is the total number of subjects The sum of squares between (SSB) can be calculated as : SSB =
2
T12 T22 T2 + + ...+ a -CF n1 n 2 na
2
where T1 is the total of the scores in group 1 squared, T2 is the total of the scores in group 2 squared, etc. n1 is the sample size for group 1, n2 is the sample size for group 2, etc. For the example data, With equal sample sizes, the formula for SSB can be simplified as:
SSB =
1 2 2 2 ( T1 + T2 +....+ Ta ) - CF n
To summarize the reasons influencing the willingness in the adoption of microinsurance. Factor analysis is a general name denoting a class of procedures used for data reduction and summarization. Factor analysis is based on the premise that in a research, there may be a large number of variables, most of which are correlated and which must be reduced to manageable level. Factor analysis is an interdependence technique that helps in determining underlying dimensions or factors that explain correlations among a set of 21
variables. Various statistics associated with factor analysis are: Factor: A factor is thus, simply a variable or construct that is not directly observable but needs to be inferred from the input variables.. Bartlett’s test of sphericity: It is a test statistic used to determine the hypothesis that variables are uncorrelated in the population implying that each variable has perfect correlation with itself but no correlation with other variables. Correlation matrix: A correlation matrix shows the simple correlations between all possible pairs of variables included in the analysis. Communality: Communality is the amount of variance a variable shares with all the other variables being considered. Eigenvalue: It represents total variance explained by each factor. Generally eigenvalues greater than 1 are used for each component. Factor loadings: These are simple correlations between the variables and the factors. Factor matrix: It contains the factor loadings of all the variables on all the factors extracted. Kaiser-Meyer-Olkin (K-M-O) measure of sampling adequacy: It is an index used to examine the appropriateness of factor analysis. Values between 0.5-1 indicate factor analysis is appropriate. For the present study, values of K-M-O measure came out to be greater than 0.5, so factor analysis was considered appropriate. Percentage of variance: This is the percentage of total variance attributed to each factor. Factor Rotation: The basic “un rotated” factor analysis usually employs principal component analysis. The objective of the principal component analysis is to determine minimum number of factors that will account for maximum variance in the data. Initial or unrotated results in factors that are difficult to interpret because the factors are correlated with many variables. So Rotation of factors can be undertaken so that factor matrix can be transformed into a simpler one that is easier to interpret. Generally varimax rotation is followed which minimizes the number of variables with high loadings on a factor, thereby enhancing interpretability of the factors. Interpretation: It is facilitated by identifying the variables that have large loadings on the same factor. That factor can be interpreted in terms of the variables that load high on it. Variables with factor loading greater than 0.5 are generally used for interpretation purposes. (Malhotra, 2008) Steps in conducting factor analysis: Coming to the analysis part, the analytical procedure systematically followed a series of steps to arrive at a solution. First of all, the objective of factor analysis was formulated. In the present study, factor analysis was applied on two questions. Objective of first question was to determine the factors which influence the willingness to adopt micro-insurance. Objective of second question was to ascertain the constraints in the adoption of micro-insurance. Then based on theory and judgement suitable 22
variables were included in the study and respondents were asked to indicate their level of agreement with the statements given to them (for both the questions) on a 5-point scale (5 = extremely important and 1 = not at all important). After that correlation matrix was constructed to see whether there were enough correlations to carry out factor analysis. Bartlett’s test of sphericity and K-M-O measure of sampling adequacy were also undertaken to judge the appropriateness of factor analysis. Preacher and MacCallum (2002) concluded that sample size depends on the level of communality of the variables and if all the communalities are above 0.6, smaller sample i.e. less than 100 may be perfectly adequate. Thus, the literature supports that sample size was adequate to carry out factor analysis. Once it was determined that factor analysis is appropriate for analyzing data, the data obtained were executed with factor analysis using principle component analysis utilizing varimax rotation method with Kaiser Normalization in order to reduce the information in many variables into a set of weighted linear combinations of those variables. In factor analysis, only those components were considered whose eigenvalue was greater than 1. Initially factor analysis was carried out on all the variables, but to get more reliable results, factor analysis was executed again by selecting only those variables from anti-image correlation matrix whose KM-O value was greater than 0.5. Interpretation was facilitated by analyzing table of rotated component matrix and total variance explained. All the factors were given appropriate names according to the variables that loaded on to each factor. Only variables with factor loading greater than 0.5 were considered for evaluation purpose. The factor analysis was executed with the help of SPSS software package. 3.5 Limitations of the study Following are the limitations of this study: 1. Due to time and resource constraints, respondents belonging to only Ludhiana city were considered for survey. A larger sample from different cities may be included in further studies. 2. Relationship between government supplier and willingness to purchase microinsurance may be studied in detail. 3. The information provided by respondents may not be fully accurate due to unavoidable biases.
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CHAPTER - IV RESULTS AND DISCUSSION This chapter presents the analysis of the primary data collected from the respondents. The study was conducted to understand and analyze the awareness and perception of respondents towards adoption of micro-insurance, and to find out the factors influencing the willingness to adopt micro-insurance. This chapter has been divided into four sections. The first section reveals the demographic profile of the respondents. The second section highlights the findings related to awareness among respondents regarding micro-insurance. The third section reveals the willingness of the respondents towards adoption of micro-insurance. The fourth section reveals the importance of constraints in the adoption of micro-insurance. 4.1 Profile of the respondents The profile of the respondents with respect to demographics like age, gender, qualification, marital status, occupation, family income, has been discussed in this section in detail. Table 6 Distribution of respondents on the basis of demographic Parameters (N=200) Demographic parameter Category Respondents n 18-20 years Age 21-30 years 31-40 years 41 and above Male Gender Female Primary School Secondary School Education Higher Secondary Diploma Graduate 65 34 34 70 18 44 32.50 17.00 17.00 35.00 9.00 22.00 22 129 30 19 135 %age 11.00 64.50 15.00 9.50 77.50
24
Unmarried Marital status Occupation Service Permanent Type of employment Seasonal Contract Based Rs 0-30,000 Rs 30,001-60000 Annual Income Rs 60001-90000 Rs 90001 and above Married Self Employed
126 74 62 138 138 33 29 13 74 80 33
63.00 37.00 31.00 69.00 69.00 16.50 14.50 6.50 37 40 16.50
The above table shows that a large majority of the respondents (75.5%) were in the age group of 18-30 year. Findings reveal that 77.5 per cent of the respondents were female, while the remaining 32.5 per cent were male. The result represents that 69 per cent of respondents studied up to higher secondary. It also depicts that 40 per cent of respondents were married while 73 per cent were unmarried. Self employed includes the persons like cart puller, rickshaw puller and an auto driver which are carrying out their business by limited means. The majority of the respondents (69%) were employed in services, 33 per cent of the respondents were self seasonally employed and rest 14.50 per cent were on contract based. The findings revealed that 56.5 per cent of the respondents had annual family income more than Rs 60,000. 4.1.1 Possessing a bank account The respondents were asked to indicate whether they have a bank account or not. Table 2 shows the distribution of respondents on the basis of having a bank account. Table 7 Distribution of respondents on the basis of possessing a bank account (N=200) Number of respondents 136 (68.00) 64 (32.00) 200 (100.00)
Having a Bank Account Yes No Total
Figures in parenthesis indicate percentage
25
The table 7 shows that majority of the respondents (68%) were having a bank account. while 32 per cent of the respondents did not possess a bank account. 4.1.2 Breadwinner of household Breadwinner is the one who has the major responsibility of running the house expenditure. The respondents were asked to indicate whether they are the breadwinner of the household will in the charge of running the house expenditure. Table 8 Distribution of respondents on the basis of being a breadwinner of Household (N=200) Breadwinner Yes No Total
Figures in parenthesis indicate percentage
Number of respondents 79 (39.50) 121 (60.50) 200 (100.00)
The above given table it is evident that majority of the respondents (69.50%) were not a bread winner. 4.1.4 Savings part of Income Table 9 shows the distribution of respondents on the basis of their savings. Respondents were asked to indicate whether they did save or not. Table 9 Savings Yes No Total
Figures in parenthesis indicate percentage
Distribution of respondents on the basis of Savings (N=200) Number of respondents 164 (82.00) 36 (18.00) 200 (100.00) The above given table below shows that larger majority of the respondents (82%) did
save. 4.1.5 Proportion of savings in income The respondents were asked to indicate what percentage of their income they save. Table 10 shows the distribution of respondents on the basis percentage of income saved.
26
Table 10
Distribution of respondents on the basis of percentage of savings (N=200)
Savings (%) 0-10% 11-20% 21 and above Total
Figures in parenthesis indicate percentage
Number of respondents 78 (39.00) 96 (48.00) 26 (13.00) 200 (100.00)
The above table reveals that larger majority of the respondents (48.00%) were saving between 11-20%, whereas 39 per cent respondents saved up to 10 per cent only. 13 per cent of the respondents were saving more than 21 per cent. 4.1.6 Risk considered while purchasing an insurance product Respondents were asked to rank in order of importance the various risks which were
considered while purchasing an insurance product. For analysis, weighted score has been calculated by multiplying the number of respondents with the rank given and thus summating the total scores. Rank 1 was then given to the risk having least summated score. The risk having second lowest summated score was given rank 2 and so on. Table 11 shows findings thus obtained. Table 11 Distribution of respondents on the basis of percentage of savings (N=200) S. No. Type of threat 1 2 3 4 5 Poor health Premature death Old age Property loss 36 31 24 11 Weighted score 2 65 40 23 28 3 31 58 41 36 4 44 19 44 78 5 24 52 68 47 Rank Weighted score 553 621 707 722 Rank 1st 2nd 3rd 4th
Figures in parenthesis indicate percentage The findings show that respondents rank poor health as the most important rish. Premature death, old age has been considered second and third most important risks respectively. 27
4.2
Level of awareness This section deals with awareness of respondents towards insurance, micro-insurance
and micro-insurance schemes. Respondents were also enquired about whether they have any micro-insurance product or not. Whether the respondents or any of the family members were having micro-insurance product was also asked. 4.2.1 Awareness towards insurance To study the level of awareness, respondents were presented with a set of statements regarding meaning of Insurance. Respondents were asked to pick the correct answers. Out of the statements, only one statement was correct. Results revealed that 51 per cent of the respondents were able to correctly answer the question regarding meaning of insurance. 4.2.2 Awareness towards micro-insurance Micro-insurance is the protection of low -income people against specific perils in exchange for regular premium payments proportionate to the likelihood and cost of the risk involved. Low-income people can use Micro-insurance, where it is available, as one of several tools (specifically designed for this market in terms of premiums, terms, coverage, and delivery) to manage their risks (Ahuja, 2005). To study the level of awareness, respondents were presented with a set of statements regarding meaning of Insurance. Respondents were asked to pick the correct answers. Out of the statements, only one statement was correct. Table 8 shows distribution of respondents on the basis of being aware of micro-insurance existence. Table 12 Distribution of respondents on the basis of being aware of microinsurance (N=200) Awareness regarding microinsurance Parameter Respondents n Awareness of microinsurance Aware Not aware Answered correct meaning of micro-insurance Yes No 84 116 74 126 %age 42.00 58.00 37.00 63.00
The above table indicates that majority of the person (58%) of the respondents were not ever aware about the existence of micro-insurance while 42 per cent of the respondents were aware that about the existence of micro-insurance. Results revealed that only 37 per cent of the respondents were able to correctly provide the meaning of micro-insurance while 28
majority of the respondents (73%) wrongly provided the meaning of insurance. 4.2.4 Possessing a micro-insurance product Table 13 shows distribution of respondents on the basis of possessing any microinsurance product. The table indicates that very large major share (83%) of the respondents were not possessing micro-insurance products. Table 13 Distribution of respondents on the basis of having a micro-insurance product (N=200) Having a micro-insurance product Yes No Total
Figures in parenthesis indicate percentage
Number of respondents 34 (17.00) 166 (83.00) 200 (100.00)
4.2.5
Awareness regarding various types of insurance Responses were further enquire about type of insurance they are aware about.
Table 14
Distribution of respondents on the basis of being aware about various types of insurance (N=200)
Types of insurance
Parameter
Respondents n %age 99.50 0.50 88.00 12.00 40.00 60.00 53.00 47.00 59.00 41.00
Life insurance
Aware Not aware Aware
199 1 176 24 80 120 106 94 118 82
Health insurance Not aware Aware Livestock insurance Not aware Aware Asset insurance Not aware Aware Crop insurance Not aware
The above table reveals that life insurance is most known insurance. A large majority of the respondents (99.5%) were aware of life insurance products. The table indicates that very a large proportion of the respondents (88%) were aware of health 29
insurance products. About fifty nine per cent of the respondents were aware of crop insurance .In case of asset insurance fifty three per cent of the respondents were aware of asset insurance. While the live stock insurance was the least known insurance only 40 per cent of the respondents were aware of livestock insurance. 4.2.6 Willingness to buy micro-insurance product Respondents were enquired about whether they were interested in buying microinsurance product. Table 15 shows distribution of respondents on the basis of willingness to buy micro-insurance. The table indicates that a large proportion of the respondents (69%) were interested in buying micro-insurance product. Table 15 Distribution of respondents on the Willingness to buy micro-insurance product (N=200) Willingness to buy micro-insurance product Yes No Total
Figures in parenthesis indicate percentage
Number of respondents 138 (69.00) 62 (31.00) 200 (100.00)
Chi-square test was applied to find out the association between age level of respondents and level of interest in buying micro-insurance products. The null hypothesis was there is no significant association between interested in buying micro-insurance and age of respondents. Results thus obtained are shown in table 15 Table 16 Distribution of respondents on the basis of age and interest in buying micro-insurance (N=200) Interested in buying Micro-insurance 18-20 years Yes No Total 15 (7.50) 7 (3.50) 22 (11.00) Age 21-30 Years 88 (44.00) 41 (21.50) 129 (64.50) 31-40 Years 21 (11.50) 9 (4.50) 30 (15.00) 41 and above 14 (7.00) 5 (2.50) 19 (9.50) Total 138 (69.00) 62 (31.00) 200 (100)
Figures in parenthesis indicate percentage Calculated chi-square value is .253 at 5 per cent level of significance Table value of chi-square is 7.81 d.f. = 3
30
The table 16 reveals that as observed chi-square value is less than table value of chisquare so it indicates that there was no significant association between age of respondents and interest in buying micro-insurance at 5 per cent level of significance. Table 17 Distribution of respondents on the basis of gender and interest in buying micro-insurance (N=200) Willingness to buy microinsurance product Yes No Total Gender Male 91 (45.50) 44 (22.00) Female 47 (23.50) 18 (9.00) Total 138 (69.00) 62 (31.00) 200 (100)
135 65 (67.50) (32.50) Figures in parenthesis indicate percentage Calculated chi-square value is .493 at 5 per cent level of significance Table value of chi-square is 3.84 d.f. = 1
The table 17 reveals that as observed chi-square value is less than table value of chisquare so it indicates that there was no significant association between gender of respondents and interest in buying micro-insurance of respondents at 5 per cent level of significance. Table 18 Distribution of respondents on the basis of education and interested in buying micro-insurance (N=200) Willingness to buy microinsurance product Yes Education Primary School 20 (10.0) 14 (7.00) 34 (17.00) Secondary School 25 (12.50) 9 (4.50) 34 (17.00) Higher Secondary 49 (24.50) 21 (10.50) 70 (35.00) Diploma 12 (6.00) 6 (3.00) 18 (9.00) Graduate 32 (16.00) 12 (6.00) 44 (22.00) Total 138 (69.00) 62 (31.00) 200 (100)
No
Total
Figures in parenthesis indicate percentage Calculated chi-square value is .253 at 5 per cent level of significance Table value of chi-square is 7.81 d.f. = 3
The table 18 reveals that as observed chi-square value is less than table value of chisquare so it indicates that there was no significant association between education of
31
respondents and interest in buying micro-insurance of respondents at 5 per cent level of significance. Table 19 Distribution of respondents on the basis of income and interest in buying micro-insurance (N=200) Willingness to buy micro-insurance product Yes Income 0-30000 10 (5.0) 3 (1.50) 13 (6.50) 30001-60000 46 (23.00) 28 (14.00) 64 (32.00) 60000-90000 60 (30.00) 20 (10.00) 80 (40.00) 90000 and above 22 (11.00) 11 (5.50) 33 (16.5) Total 138 (69.00) 62 (31.00) 200 (100)
No
Total
Figures in parenthesis indicate percentage Calculated chi-square value is 3.429 at 5 per cent level of significance Table value of chi-square is 7.81 d.f. = 3
The table 19 reveals that as observed chi-square value is less than table value of chisquare so it indicates that there was no significant association between income of respondents and interest in buying micro-insurance of respondents at 5 per cent level of significance. 4.2.7 Awareness towards insurance companies To study the level of awareness towards insurance company’s respondents were asked to name the three companies which at first come to their mind. Results revealed that 20 per cent of the respondents were not aware of any insurance company. One third of the respondents were aware of Life Insurance Corporation (LIC) of India. Next, twelve per cent of the respondents were aware of ICICI prudential life. While Bajaj, Birla and Aviva were the other private sector insurance companies which were known to respondents. 4.2.8 Awareness towards various micro-insurance schemes To study the level of awareness regarding micro-insurance schemes respondents were presented with a set of statements covering various schemes offered by public sector companies as well as private sector companies. Respondents were asked to mark the microinsurance schemes which they were aware of. Results revealed that majority of the respondents were not aware of even a single micro-insurance scheme. Micro-insurance schemes offered by public sector companies were more prevalent among respondents. Microinsurance schemes offered by LIC and health micro-insurance schemes were the schemes about which more consumers were aware.
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4.3
Parameters influencing the willingness to adopt micro-insurance This section presents analysis of finding regarding perceptions of respondents toward
parameters willingness to adopt the micro-insurance. Respondents were asked to give their response on a five-point Likert scale as ‘extremely important’, ‘more important’, ‘important’, ‘less important’ and ‘not all important.’ Table 20 S. No. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 Parameters influencing the willingness to adopt Micro-insurance Mean score 4.38 4.02 4.00 4.00 3.90 3.89 3.88 3.87 3.75 3.67 3.64 3.50 3.45 3.40 3.31 3.28 3.25 3.22 3.12 (N=200) Standard deviation 0.74 0.80 0.84 0.90 0.94 0.84 0.89 0.93 0.93 0.93 0.94 0.97 1.15 1.00 1.12 1.07 0.96 1.00 1.06
Parameters Trust on the insurance providers Premium Availability of suitable product Income earned Awareness of product Corporate image Services provided by the insurance companies Claim settlement procedure Flow of Income Claim Ratio Premium flexibility Documentation Government support Age of the insurer Word of mouth High claim rejection Refusal on the basis of health conditions Marketing by agents or company officials Recommendation of friends and relatives
Mean score analysis indicates that the major parameters that influence willingness to adopt micro-insurance were ‘trust on insurance companies (4.38)’, ‘income of the earner 33
(4.05)’, ‘availability of suitable product (4.05)’, ‘premium (3.90)’, ‘awareness of the product ( 3.88)’, ‘service provided by insurance companies (3.7)’, ‘non availability of suitable product (3.45)’, ‘non flexibility of premium (3.4)’,‘Old age (3.36)’ ‘non accessibility due to remote area (3.3)’ as important parameters influencing the adoption of micro-insurance. Mean score for majority of the statements was greater than 3 indicating that respondents by and large tend to agree with the statements. To identify the major factors influencing the willingness to adopt micro-insurance, factor analysis was performed. Further in order to test the suitability of data for factor analysis, reliability analysis was carried out with the help of Cronbach’s alpha, which is a measure of consistency. For this study, reliability coefficient (alpha) came out to be more than recommended lower limit of 0.7. Kaiser-Meyer-Olkin Measure of sampling adequacy and Bartlett’s test of sphericity favoured the appropriateness of factor analysis. K-M-O value for this study was 0.763. Bartlett’s test of sphericity was used to test the hypothesis that the variables were uncorrelated in the population. A large value of the test statistic (as shown in table 21) favoured the rejection of null hypothesis and showed that statistically significant number of correlations existed among the variables. The results have been presented in Table 21. Table 21 K-M-O and Bartlett’s Test of Sphericity 0.763 835.188 171 .000
Kaiser-Meyer-Olkin Measure of Sampling Adequacy Bartlett's Test of Sphericity Approx. Chi-Square df Sig.
Table 22 reveal the result that first factor named as Document and Government support, accounts for the largest proportion (11.933%) of total explained variance. Three variables like ‘documentation’, ‘refusal on the basis of health’ and ‘government support’ loaded on this factor. Factor 2 explained 11.624 of total explained variance and was named as ‘income’. Four items namely ‘income of the earner’, ‘friend recommendation’ ‘flow of income’ and ‘premium’ loaded on this factor. Factor 3 explained 10.031 of total variance and was named as ‘Trust and Customer service’. Three items namely ‘trust on insurance companies’, ‘service provided by insurance’, ‘claim settle procedure’ loaded on this factor. Factor 4 explained 10.038 of total variance and was named as ‘product availability and awareness’. Four items namely ‘age of the buyer’, ‘availability of suitable product’, ‘claim ratio’, ‘awareness of the product’ loaded on this factor.
34
Table 22
Rotated component matrix Factors
Parameters
DO and GS 0.802 0.601 0.546 0.44 0.023 0.22 0.144 -0.125 -0.037 0.122 0.305 -0.109 0.265 0.283 0.297 -0.079 0.024 -0.07 0.561 11.933 11.933
INC 0.107 0.012 0.076 0.261 0.769 0.659 0.649 0.545 0.128 -0.074 -0.126 0.208 0.39 0.287 -0.185 -0.104 0.155 -0.015 -0.011 11.624 23.557
TCS 0.069 -0.001 0.007 0.379 -0.128 0.173 -0.002 0.156 0.771 0.735 0.503 0.211 0.208 -0.027 0.275 0.051 0.341 -0.06 0.262 10.031 33.888
PAA -0.016 0.221 0.419 0.318 0.192 -0.176 0.149 0.208 -0.025 0.238 0.234 0.629 0.528 0.517 0.515 0.196 0.231 0.152 -0.12 10.038 43.936
Documentation Refusal on the basis of health Government support Marketing by agents or company officials Income earned Recommendation by friends or relatives Flow of the income Premium Trust on the insurance companies Service provided by the insurance companies Claim settlement procedure Availability of suitability product Awareness of the product Age of the product buyer Claim ratio High claim rejection Premium flexibility Word of mouth Corporate image Variation Explained (%) Cumulative variance explained (%)
CR and PF -0.003 0.416 -0.083 0.094 0.059 -0.354 0.216 0.32 -0.046 0.058 0.287 0 -0.148 0.171 -0.025 -0.709 0.546 0.034 -0.008 7.411 51.337
WM 0.074 -0.053 -0.199 0.071 -0.012 0.223 -0.177 0.015 -0.08 0.054 0.205 0.146 -0.1 0.015 0.336 0.022 0.123 0.852 0.561 7.296 58.637
Extraction Method: Principal Component Analysis. 6 Components extracted Marketing by company agents and High claim rejection ignored due to factor loading less than 0.5 DO and GS: Document and government support, INC: Income, TCS: Trust and customer service; PAA: Product awareness and availability, CR and PF: Claim ratio and product flexibility, WM: Word of mouth
35
4.4
Constraints in the adoption of micro-insurance This section presents the analysis of constraints faced by respondents in adopting the
micro-insurance. To analyze this, respondents were presented with a set of statements related to constraints and they were asked to give their response on a five-point Likert scale as ‘Extremely Important’, ‘More Important’, ‘Important’, ‘Less Important’ and ‘Not all Important.’ Table 23 S. No. 1 2 3 4 5 6 7 8 9 10 11 12 Constraints in the adoption of Micro-insurance (N=200) Statement Lack of trust Variable income High cost Awareness of product Not able to save Low income Non availability of suitable product Non flexibility of premium Non accessibility due to remote area Old age Refusal by insurer to offer insurance schemes on health grounds Never felt for the need of insurance Mean score 3.95 3.90 3.85 3.77 3.77 3.75 3.45 3.44 3.37 3.36 3.17 2.84 S.D. 1.05 .92 1.04 .96 .92 1.04 .97 1.01 1.10 1.09 1.01 1.20 Z-value 12.67* 13.79* 11.49* 11.37* 11.80* 10.17* 6.62* 6.12* 4.71* 4.65* 2.37* -1.87
*Significant at 5% level of significance (z-critical =1.96) From the above table, mean score analysis indicates that the major constraints in the adoption of micro-insurance were ‘lack of trust (3.95)’, ‘variable income (3.90)’, ‘High cost (3.85)’, ‘awareness about the product (3.78)’, ‘ not able to save (3.77)’, ‘low income of the respondent (3.7)’, ‘non availability of suitable product (3.45)’, ‘non flexibility of premium (3.4)’, ‘Old age (3.36)’, ‘non availability due to remote area (3.3). Mean score for majority of the statements was greater than 3 indicating that respondents by and large tend to agree with the statements. Z-test results were significant for all the parameters except the parameter ‘never felt the need for insurance, indicating that the observed mean value for the statement was significantly different from the assumed mean value of 3 at 5 per cent level of significance. Also the findings regarding differences in perception of respondents categorised on the basis of demographic variables (age, gender, education, income) towards constraints in the 36
adoption of micro-insurance have been presented below. Table 24 Differences in the perception of respondents categorised on the basis of age regarding constraints faced in the adoption of micro-insurance
Parameters Age category Up to 20 Variable income 21 -30 31-40 41 and above Up to 20 Old age 21 -30 31-40 41 and above Up to 20 Awareness of insurance 21 -30 31-40 41 and above Up to 20 21 -30 31-40 41 and above Up to 20 21 -30 31-40 41 and above Up to 20 Low income 21 -30 31-40 41 and above Up to 20 21 -30 31-40 41 and above Up to 20 Non availability of suitable product 21 -30 31-40 41 and above Up to 20 21 -30 31-40 41 and above N 22 129 30 19 22 129 30 19 22 129 30 19 22 129 30 19 22 129 30 19 22 129 30 19 22 129 30 19 22 129 30 19 22 129 30 19 Mean 3.86 3.93 3.90 3.73 3.72 3.17 3.86 3.42 4.00 3.69 3.80 4.00 3.86 3.68 4.00 3.89 3.86 3.69 4.13 4.42 3.90 3.62 4.00 4.05 3.22 3.48 3.56 3.15 3.59 3.41 3.53 3.42 2.86 3.17 3.46 3.05 S.D. 1.24 0.81 0.99 1.14 1.42 0.99 1.07 1.07 0.97 0.97 1.12 0.47 0.94 0.88 1.14 0.73 1.20 1.03 1.00 0.69 0.92 1.05 1.11 0.97 0.61 1.09 1.04 0.76 1.25 0.92 1.00 .90 0.56 0.98 1.38 0.84 0.27 0.844 1.86 0.136 1.02 0.381 4.50** 0.004 0.27 0.844 F Statistic p-value
Not able to save
1.20
0.309
High cost
3.68**
0.013
Non flexibility of premium
1.06
0.365
Refusal by insurer to offer insurance schemes on health grounds
1.62
0.184
37
Non accessibility due to remote area
Up to 20 21 -30 31-40 41 and above Up to 20 21 -30 31-40 41 and above
22 129 30 19 22 129 30 19
3.77 3.27 3.66 3.05 4.00 3.86 4.13 4.21
1.30 1.04 1.18 1.02 1.27 1.06 0.97 0.85
2.55***
0.057
Lack of trust
1.00
0.392
Up to 20 22 3.04 1.49 21 -30 129 2.94 1.16 Never felt for the need of 2.44*** insurance 31-40 30 2.60 1.19 41 and above 19 2.26 0.99 *Significant at 1 % level, **Significant at 5% level, ***Significant at 10% level
0.065
One-way ANOVA test was applied to all the parameters and the results are shown in the above table. Results reveal that significant differences has been found regarding perception of respondents categorised on the basis of age, towards constraints ‘high cost’, ‘old age’, ‘non- accessibility due to remote area’, and ‘never felt for the need of insurance’. Further, mean score analysis revealed that respondents above consider ‘high cost’ and ‘old age’ as a major constraint in the adoption of micro-insurance. While, respondents up to 20 years consider ‘non accessibility due to remote area’ as a major constraint. Table 25 Differences in the perception of respondents categorised on the basis of Gender regarding constraints faced in the adoption of micro-insurance Parameters Gender Male Variable income Female Male Old age Female Male Awareness of insurance Female Male Not able to save Female Male High cost Female Male Low income Female 38 N 135 65 135 65 135 65 135 65 135 65 135 65 Mean 3.82 4.06 3.13 3.83 3.74 3.83 3.68 3.93 3.77 4.00 3.76 3.73 S.D. 0.91 0.93 1.11 19.49* 0.87 1.05 0.32 0.74 0.97 0.78 1.07 0.96 1.13 0.85 1.99 .160 3.24*** .073 .571 .000 2.76 .098 F Statistic pvalue
0.02
.878
Male Non flexibility of premium Non availability of suitable product Female Male Female
135 65 135 65 135 65 135 65 135 65 135 65
3.30 3.72 3.43 3.49 3.11 3.27 3.24 3.63 4.02 3.80 2.88 2.75
1.06 7.73** 0.83 1.01 0.88 1.05 0.92 1.16 0.94 1.03 1.10 1.20 1.21 0.49 .484 1.93 .165 1.07 .301 0.14 .707 .006
Refusal by insurer to offer Male insurance schemes on health Female grounds Male Non accessibility due to remote area Lack of trust Female Male Female Up to 20 Never Felt need for insurance 21 -30
5.44**
.021
*Significant at 1 % level, **Significant at 5% level, ***Significant at 10% level
One-way ANOVA test was applied to all the parameters and the results are shown in the above table. Results reveal that significant differences has been found regarding perception of respondents categorised on the basis of a gender, towards constraints ‘not able to save’, ‘old age’, ‘non accessibility due to remote area’, and ‘non flexibility of the
premium’. Further, Mean score analysis revealed that female respondents consider ‘‘not able to save’, ‘old age’, ‘non accessibility due to remote area’, and ‘non flexibility of the premium’ as a major constraint in the adoption of micro-insurance. Table 26 Differences in the perception of respondents categorised on the basis of Education regarding constraints faced in the adoption of microinsurance Education Primary School Secondary School Variable Income Higher Secondary Diploma Graduate Primary School Secondary School Old Age Higher Secondary Diploma Graduate N 34 34 70 18 44 34 34 70 18 44 Mean 3.76 4.00 3.91 3.83 3.95 3.47 3.20 3.54 3.50 3.04 S.D. 1.12 0.95 0.95 0.70 0.77 1.23 1.14 0.98 1.09 1.05 1.75 0.140 0.33 0.851 F Statistic pvalue
Parameters
39
Primary School Secondary School Awareness of insurance Higher Secondary Diploma Graduate Primary School Secondary School Not able to save Higher Secondary Diploma Graduate Primary School Secondary School High Cost Higher Secondary Diploma Graduate Primary School Secondary School Low Income Higher Secondary Diploma Graduate Primary School Secondary School Non Flexibility of premium Higher Secondary Diploma Graduate Primary School Secondary School Non Availability of Suitable product Higher Secondary Diploma Graduate Primary School Refusal by insurer to offer insurance schemes on health grounds Secondary School Higher Secondary Diploma Graduate 40
34 34 70 18 44 34 34 70 18 44 34 34 70 18 44 34 34 70 18 44 34 34 70 18 44 34 34 70 18 44 34 34 70 18 44
3.97 3.91 3.72 3.72 3.61 3.67 4.02 3.67 3.77 3.79 4.08 4.17 3.90 3.22 3.59 4.29 4.02 3.50 3.22 3.75 3.32 3.26 3.52 3.44 3.52 3.38 3.44 3.54 3.55 3.34 3.20 3.00 3.31 3.22 3.02
0.75 0.62 1.12 1.07 0.99 0.94 0.90 0.91 0.80 0.97 1.05 0.86 0.98 0.94 1.16 0.87 0.90 0.94 1.26 1.14 0.94 0.79 1.07 1.04 1.13 0.98 0.82 1.03 0.92 1.01 0.84 1.04 1.00 0.80 1.19 0.84 0.497 0.38 0.817 0.56 0.688 5.47* 0.000 3.81** 0.005 0.96 0.427 0.88 0.476
Primary School Secondary School Non accessibility due to Remote Area Higher Secondary Diploma Graduate Primary School Secondary School Lack of trust Higher Secondary Diploma Graduate Primary School Never Felt need for the insurance Secondary School Higher Secondary Diploma Graduate
34 34 70 18 44 34 34 70 18 44 34 34 70 18 44
3.32 3.08 3.72 3.16 3.13 4.44 3.85 3.81 4.00 3.84 2.79 3.02 2.84 3.11 2.61
1.06 1.23 1.03 1.20 1.00 0.66 1.23 1.05 1.13 1.07 1.14 1.19 1.26 1.23 1.14 0.83 0.504 2.37*** 0.054 3.16* 0.015
*Significant at 1 % level, **Significant at 5% level, ***Significant at 10% level
One-way ANOVA test was applied to all the parameters and the results are shown in the above table. Results reveal that significant differences has been found regarding perception of respondents categorised on the basis of a education, towards constraints ‘high cost’, ‘low income’, ‘lack of trust’ and ‘non accessibility due to remote area’. Further, mean score analysis revealed that respondents having education up to primary school consider ‘low income’ as a major constraint. ‘Non accessibility due to remote area’ was major constraint for the respondents who have attained qualification up to higher secondary. Table 27 Difference in the perception of respondents categorised on the basis of Income regarding constraints faced in the adoption of micro-insurance Parameters Income category (Rs) 0-30,000 30,001-60000 60001-90000 90001 and above 0-30,000 30,001-60000 Old age 60001-90000 90001 and above 41 N 13 74 80 33 13 74 80 33 Mean 4.07 4.00 3.85 3.75 3.38 3.56 3.25 3.15 S.D. 0.75 0.93 0.90 1.03 0.96 1.12 1.09 1.03 1.57 0.197 0.77 0.508 F Statistic pvalue
Variable income
0-30,000 Awareness of insurance 30,001-60000 60001-90000 90001 and above
0-30,000 Not able to save 30,001-60000 60001-90000 90001 and above 0-30,000 High cost 30,001-60000 60001-90000 90001 and above 0-30,000 Low income 30,001-60000 60001-90000 90001 and above 0-30,000 Non flexibility of premium 30,001-60000 60001-90000 90001 and above 0-30,000 Non availability of suitable product 30,001-60000 60001-90000 90001 and above 0-30,000 Refusal by insurer to offer insurance schemes on health grounds 30,001-60000 60001-90000 90001 and above 0-30,000 Non accessibility due to Remote Area 30,001-60000 60001-90000 90001 and above 0-30,000 Lack of trust 30,001-60000 60001-90000 90001 and above
13 74 80 33
13 74 80 33 13 74 80 33 13 74 80 33 13 74 80 33 13 74 80 33 13 74 80 33 13 74 80 33 13 74 80 33
3.53 3.78 3.88 3.57
3.53 3.83 3.78 3.66 3.46 4.20 3.76 3.42 4.00 3.97 3.63 3.45 2.61 3.47 3.50 3.54 3.23 3.60 3.40 3.33 3.15 3.51 3.03 2.72 2.84 3.43 3.36 3.45 2.92 4.06 4.01 3.93
1.05 0.88 0.98 1.06
0.51 0.81 1.01 1.05 0.66 0.95 1.09 1.03 0.40 0.97 1.12 1.09 1.12 0.95 1.04 0.93 0.43 0.96 1.02 0.98 0.89 1.03 0.92 1.00 1.40 1.04 1.10 1.12 1.60 1.05 0.96 0.86 4.71** 0.003 1.11 0.345 5.78* 0.001 1.10 0.348 3.19** 0.025 2.59*** 0.053 5.81* 0.001 0.55 0.649
1.09
0.351
42
0-30,000 Rs Never felt need for the insurance 30,001-60000 Rs 60001-90000 Rs 90001 and above
13 74 80 33
2.84 2.50 3.05 3.09
1.34 1.25 1.10 1.15 3.36** 0.020
*Significant at 1 % level, **Significant at 5% level, ***Significant at 10% level
One-way ANOVA test was applied to all the parameters and the results are shown in the above table. Results reveal that significant differences has been found regarding perception of respondents categorised on the basis of income, towards constraints ‘high cost’, ‘low income’, ‘non flexibility of premium’, ‘lack of trust’, ‘refusal by insurer to offer insurance schemes on health grounds’ and ‘never felt for the need of insurance’. Further, Mean score analysis revealed that respondents having annual less than 60,000 per annum consider ‘high cost’, ‘low income’ and ‘lack of trust’ as a major constraint. ‘Non accessibility due to remote area’ was major constraint for the respondents earning more than Rs 90,000 per annum. 4.5 Discussions This section presents a discussion of the major findings revealed by the study. The first objective of the study was to determine the awareness among respondents towards microinsurance and factors influencing the willingness to adopt micro-insurance Results revealed poor health were considered most important risks while purchasing an insurance product resp. Larger majority (58%) of the respondents were not aware of micro-insurance. Most of the respondents (83%) were not possessing micro insurance products. Life insurance had most awareness among respondents followed by health insurance. 63 per cent respondents were interested in buying micro-insurance product. Life Insurance Company has got most awareness among respondents. Larger majority of the respondents were not aware of even a single micro-insurance scheme. ‘Trust on insurance companies’ and ‘income of the earner’ were two major factors which influence the willingness to adopt micro insurance. So companies should think twice and scrutinize each filed claimed very carefully before rejecting so as to build trust among people as ‘lack of trust’ has been considered major constraint in the adoption of micro-insurance. Second objective of the study was to study the various constraints in the adoption of micro-insurance. Results of the study revealed that respondents consider major constraints in the adoption of micro insurance were ‘lack of trust’, ‘variable income’, ‘high cost’ and awareness about the product’. It was found that there were significant differences in the perception of respondents categorized on the basis of income, towards constraints ‘high cost’, ‘low income’. Respondents having annual income less than Rs 60,000 per annum consider ‘high cost’, ‘low income’ and ‘lack of trust’ as a major constraint. Result indicated that
43
female respondents consider ‘not able to save’, ‘old age’, ‘on- accessibility due to remote area’, and ‘non-flexibility of the premium’ as major constraints in the adoption of micro insurance. Most of the respondents were willing to buy micro-insurance but due to constraints like ‘trust on insurance companies’ and ‘variable income’, ‘high cost ’, ‘awareness about the product’, ‘not able to save’ , ‘non- availability of suitable product’, and ‘non flexibility of premium’, they were not able to adopt micro-insurance products. So, suitable products, taking into account the low income levels prevalent in our country, should be developed should have enough flexibility regarding payments. Documentation should be kept as simple as possible for issuing a micro-insurance policy
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CHAPTER - V
SUMMARY
In this chapter, a brief summary of the study has been presented, so as to understand the implications of the findings. The chapter also discusses recommendations and scope of the study. 5.1 Summary India is the country currently having the most dynamic micro-insurance sector in the world. Liberalization of the economy and the insurance sector has created new opportunities for insurance to reach the vast majority of the poor, including those working in the informal sector. Even so, market penetration is largely driven by supply, not demand (Anonymous, 2006). Although the type of risks faced by the poor such as that of death, illness, injury and accident, are no different from those faced by others, they are more vulnerable to such risks because of their economic circumstance (Ahuja and Khasnobis, 2005). Micro-insurance is specifically designed for the protection of low-income people, with affordable insurance products to help them cope with and recover from common risks. It is a market-based mechanism that promises to support sustainable livelihoods by empowering people to adapt and withstand stress (Anonymous, 2006). In the context of health contingency, for example, a World Bank study (Peters et al 2002), reports that 25 per cent hospitalized Indians fall below the poverty line as a result of their stay in hospitals. The same study reports that more than 40 per cent of hospitalized patients take loans or sell assets to pay for hospitalization (Ahuja and Khasnobis, 2005). There are some 14 million adults are covered by life micro-insurance in India. In a country with some 120 million families living on less than $2 a day, this is a very small proportion of the potential micro-insurance market and an indication of an untapped market of nearly US$2 billion (Anonymous, 2007). There is a need to study the awareness about micro-insurance, analyze the factors affecting the willingness to adopt micro-insurance and identify the constraints in the adoption of micro-insurance. So, the present study was aimed to achieve the following specific objectives: 1 To analyze the perception of respondents toward willingness to adopt microinsurance 2 To examine the constraints in the adoption of micro-insurance The population of the study comprised respondents from both informal and formal sector. Individuals belonging to low income group comprised the major proportion of the sample. A sample of 200 respondents was selected on convenience basis and willingness of respondents to share information. 45
To meet the objectives of the study primary data were collected. Primary data were collected through a pre-designed, structured and non-disguised questionnaire. Various studies were reviewed to have a thorough understanding about various parameters to be included in questionnaire and accordingly a self-administered and structured questionnaire was designed to collect information from the respondents. Questions were specifically designed to get in-depth information about the profile of the respondents, awareness level of respondents towards insurance, kinds of insurance products, micro-insurance, and various micro schemes constraints faced in the adoption of micro-insurance. Questions related to factors influencing willingness to adopt were also included. Both open ended as well as close ended questions were asked. Respondents were also asked multiple choices, dichotomous and scale based questions. For scale based questions, respondents were asked to provide their responses on a five-point Likert scale indicating their level of agreement, where ‘5’ showed ‘extremely important’, ‘4’ as ‘very important’, ‘3’ as ‘important’, ‘2’ as ‘less important’ and ‘1’ as ‘not at all important.’ 5.2 Findings of the study This section deals with findings and conclusions drawn from the study. 5.2.1 ? Awareness about micro-insurance among respondents Results revealed that risk of life and poor health were considered most important risks while purchasing an insurance product respectively. ? Results revealed that 51 per cent of the respondents were aware with the exact meaning of insurance while almost half share i.e. 49 per cent was not aware. ? Larger majority (58%) of the respondents were not aware of micro-insurance. Besides being aware of micro-insurance most of the respondents were not able to provide the exact meaning of micro-insurance. ? The results that that very large major share (83%) of the respondents were not possessing micro-insurance products, While only 17 per cent of the respondents were having any kind of micro-insurance products. ? Life insurance had most awareness among respondents followed by health insurance. The result indicates that very large proportion of the respondents (88%) was aware of health insurance products. ? Life Insurance Company has got most awareness among respondents followed by ICICI prudential life and Birla sun life. ? Larger majority of the respondents were not aware of even a single micro-insurance scheme. Life micro-insurance and health micro-insurance schemes were having more awareness among respondents then other kinds of insurance.
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5.2.2 Factors influencing the willingness to adopt micro-insurance ? The results that large proportion of the respondents (69%) was interested in buying micro-insurance products. ? Results revealed that respondents consider ‘trust on insurance companies (4.38)’, ‘income of the earner (4.05)’, ‘availability of suitable product (4.05)’, ‘premium (3.90)’, ‘awareness of the product ( 3.88)’, ‘service provided by insurance companies (3.7)’, ‘non availability of suitable product (3.45)’, ‘non flexibility of premium (3.4)’,‘Old age (3.36)’ ‘non accessibility due to remote area (3.3)’ as important parameters influencing the adoption of micro-insurance. ? The factor analysis results highlighted that respondents consider ‘document and government support’, ‘income’, ‘trust and customer service’, ‘product awareness and availability’, ‘claim ratio and product flexibility’, ‘word of mouth’ as important factors influencing the adoption of micro-insurance 5.2.3 ? Constraints in the adoption of micro-insurance Results revealed that respondents consider major constraints in the adoption of microinsurance were ‘lack of trust (3.95)’, ‘variable income (3.90)’, ‘High cost (3.85)’, ‘awareness about the product (3.78)’, ‘ not able to save (3.77)’, ‘low income of the respondent (3.7)’, ‘non availability of suitable product (3.45)’, ‘non flexibility of premium (3.4)’, ‘Old age (3.36)’, ‘non availability due to remote area (3.3)’ ? Results reveal that there were significant differences in the perception of respondents categorized on the basis of age, towards constraints ‘high cost’, ‘old age’, ‘non accessibility due to remote area’, and ‘never felt for the need of insurance’. Further, mean score analysis revealed respondents above 20 years consider ‘high cost’ and ‘old age’ as major constraints in the adoption of micro-insurance. ? Also it was found that there were significant differences in the perception of respondents categorized on the basis of income, towards constraints ‘high cost’, ‘low income’, and ‘non flexibility of premium’. Further, Mean score analysis revealed that respondents having annual income less than Rs 60,000 per annum consider ‘high cost’, ‘low income’ and ‘lack of trust’ as a major constraint. ? Result indicated that female respondents consider ‘not able to save’, ‘old age’, ‘non- accessibility due to remote area’, and ‘non-flexibility of the premium’ as major constraints in the adoption of micro-insurance.
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5.2.5
Conclusion
Thus the present study revealed that majority of the respondents was unaware about the micro-insurance and various micro-insurance schemes launched by government. Respondents consider ‘document and government support’, ‘income’, ‘trust and customer service’, ‘product awareness and availability’, ‘claim ratio and product flexibility’, ‘word of mouth’ as important factors influencing the adoption of micro-insurance. Most of the respondents were willing to buy micro-insurance but due to constraints like ‘trust on insurance companies’ and ‘variable income’, ‘high cost ’, ‘awareness about the product’, ‘not able to save’ , ‘nonavailability of suitable product’, and ‘non flexibility of premium’, they were not able to adopt micro-insurance products. 5.3 Recommendations of the study Majority of the respondents were not aware about the micro-insurance schemes launched by government, public sector and private sector companies. Therefore, steps need to be undertaken by government to create awareness among targeted people about the existing schemes so that benefits of the schemes reach in right hands. Awareness might be created by launching promotional programs on community radio, T.V etc. Also companies should think twice and scrutinize each filed claimed very carefully before rejecting so as to build trust among people as ‘lack of trust’ has been considered major constraint in the adoption of microinsurance. Also suitable products, taking into account the low income levels prevalent in our country, should be developed should have enough flexibility regarding payments. Documentation should be kept as simple as possible for issuing a micro-insurance policy. 5.4 Scope for future research A few areas where there is scope for further research are mentioned below: 1. Future studies may include larger samples from other cities. 2. Impact of government support and adoption of micro-insurance may be studied in future studies.
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CHAPTER VI REFRENCES
Ahuja R and Khasnobis B G (2005) Micro-insurance in India: trends and strategies for further extension, working paper 162, Indian Council for Research on International Economic Relations, New Delhi. Ahuja R and Jutting J (2007) Are the poor too poor to demand health insurance. J Finance 6 : 1-20. Akotey O J, Osei K A and Albert G (2011) The demand for micro-insurance in Ghana. J Risk Fin 12: 182-94. Anonymous (2005) Insurance products provided by insurance companies to the disadvantaged groups in India, working paper 1, International labour office, Geneva. Retrieved on April 1, 2012 from http://www.microinsurancenetwork.org/publication /fichier/_Microinsurance_and_MFI _ Case_Study_15.pdf Anonymous (2005a) India: An inventory of micro insurance schemes, working paper 2, International labour office, Geneva. Retrieved on April 1,2012 from http://www.microinsurancecentre.org /resources/documents/doc_download/90-indiaan-inventory-of-micro-insurance-schemes.html Anonymous (2005b) Insurance Regulatory and Development Authority (MicroInsurance) Regulations, Insurance Regulatory and Development Authority. Retrieved on Feburary 4, 2012 from http://www.irdaindia.org/regulations/IRDAMirco-Ins_reg-2005.pdf. Anonymous (2006) Micro-Insurance demand and market prospects, Federal Ministry for Economic Cooperation and Development. Retrieved on September 26, 2011 from http://www.sggwrites.com/docs/GuthridgeGould_11_Microinsurance%20India.pdf. Anonymous (2007) Building security for the poor: potential and prospects for microinsurance in India, United Nations Development Programme, Colombo. Retrieved on March 5, 2012 from http://asia-pacific.undp.org/practices/HDRU/documents/publications/P1 108.pdf Anonymous (2007a) Issues in regulation and supervision of microinsurance, International association of insurance supervisors. Retrieved on Feburary 14, 2012 from http://www.iaisweb.org/__temp/Issues_Paper_in_regulation_and_supervsion_of_mic roinsurance__June_2007.pdf Anonymous (2008) Micro-Insurance regulation in the Indian financial landscape, MicroCredit Ratings International Limited, M-CRIL. Retrieved on September 26, 2011 from http://www.mcril.com/BackEnd/ModulesFiles/Publication/Micro_Insurance_R egulation_In_The_Indian_ Financial_Landscape.pdf. Anonymous (2009) Annual report 2008-09, Insurance Regulatory and Development Authority. Retrieved on March 19, 2012 from http://www.Irdaindia.org/annualre port09/annual_rep _eng _09.pdf Anonymous (2010) Compendium of Microinsurance Products, All India Artisans and Craftworkers Welfare Association, New Delhi. Retrieved on March 30, 2012 from http://www.Aiacaonline .org/pdf/Compendium-Microinsurance-Products.pdf 49
Anonymous (2011) Annual report 2010-11, Insurance Regulatory and Development Authority. Retrieved on March 20, 2012 from http://www.irda.gov.in/ADMINCMS /cms/frmGeneral_Layout.aspx?page=PageNo1583&flag=1&mid=Annual+reports+ %3e%3e+Annual+reports+of+the+Authority. Anonymous (2011a) Insurance in emerging markets: growth drivers and profitability, Swiss reinsurance company, economic research and consulting, Switzerland. Retrieved on March 5, 2012 from http://j7.agefi.fr/documents/liens/201112/21-liaoiblsgg8yhw6.pdf Anonymous (2012) History of insurance in India, Insurance Regulatory and Development Authority Retrieved on January 9, 2012 from http://www.irda.gov.in/ADMINCMS /cms/NormalData_L ayout.aspx?page=PageNo4&mid=2 Anonymous (2012a) Microinsurance, Retrieved on February 11, 2012 from http://www .banknetindia. com /finance/imicro.htm Anonymous (2012b) Micro insurance, Chapter 11. Retrieved on February 12, 2012 from http://www.nabard.org/pdf/report_financial/Chap_XI.pdf Anonymous (2012c) Compendium of Microinsurance Products, Retrieved on March 1, 2012 from http://www.srtt.org/institutional_grants/pdf/compendium.pdf Arun T and Steiner S (2008) Micro-Insurance in the context of social protection, working paper no. 55, Brooks World Poverty Institute, University of Manchester , Manchester. Banthia A, Johnson S, McCord M J and Mathews B (2009) Microinsurance that works for women: making gender-sensitive microinsurance programs, working paper 3, International Labour Office, Geneva. Bendig M and Arun T (2011) Enrolment in micro life and health insurance: Evidence from Sri Lanka, IZA Discussion Paper, 1-29. Bhat R and Jain N (2006) Factors effecting the demand for health insurance in a micro insurance scheme, working paper 2, Indian Institute of Management, Ahemdabad. Cai H, Chen Y, Fang H and Zhou L A (2009) Microinsurance, trust and economic development: evidence from a randomized natural field experiment, working paper 15396, National Bureau of Economic Research, Cambridge. Churchill C (2006) What is insurance for the poor? In Churchill, C. (ed.). Protecting the poor, A micro-insurance compendium, International Labour Organisation, Geneva. Coydon M A and Molitor A V (2011) Commercial insurer in microinsurance, Micro Insurance Network. Retrieved on March 5, 2012 from http://www.microinsurancene twork.org/publication/fichier/MiN_Commercial_insurers_study_2011.pdf Dercon S, Kirchberger M, Gunning J W and Platteau J P (2008) Literature review on microinsurance, working paper 1, International Labour Office, Geneva. Heenkanda S (2011) Prospective demand for an index-based micro insurance in Sri Lanka. Asia Pacific J Social Sci, 3: 1-31. Jim Roth and Michael J McCord (2008) Agricultural microinsurance global practices and prospects, The MicroInsurance Centre, United states of America. Leatherman S, Christensen L J and Holtz J (2010) Innovations and barriers in health microinsurance, working paper 12, International Labour Office, Geneva. 50
Matul M, Jaleran C T, and Kelly E (2011) Improving client value from microinsurance: Insights from India, Kenya, and the Philippines, working paper 12, International labour office, Geneva. Mausley P (2009) Assessing the success of microinsurance programmes in meeting the insurance needs of the poor, working Paper 84, University of Sheffield. Mittal N K (2009) Micro insurance, The institute of Chartered Accountants of India, New Delhi. Retrieved on January 15, 2012 from http://220.227.161.86/20959microinsur ance.pdf Morelli E, Onnis G A, Ammann W J and Sutter J (2010) Microinsurance an innovative tool for risk and disaster management, Global Risk Forum Davos, Italy. Mukherjee P (2012) Microinsurance product types in India, MicroSave India focus note 86. Retrieved on March 15, 2012 from http://www.microsave.org/sites/files/technical Briefs/indiaFocusNotes/IFN_86_Microinsurance_Product_Types_in_India.pdf Mukherjee P (2012a) Microinsurance in India: The Evolution of Market Trends, MicroSave India focus note 87. Retrieved on March 15, 2012 from http://www.microsave.org/sit es/files/technicalBriefs/indiaFocusNotes/IFN_87_MI_in_IndiaThe_Evolution_of_Ma rket_Trends.pdf Paul M (2009) Assessing the success of microinsurance programmes in meeting the insurance needs of the poor, DESA working Paper 84, Economics and social affairs. Peters D et al (2002). Better Health Systems for India’s Poor: Findings, Analysis, and Options,The World Bank, Washington DC. Rajeev Ahuja and Johannes Jütting (2004) Are the poor too poor to demand health insurance? J Microfin,6 Roth J, Mccord M J and Liber D (2007) The landscape of micro-insurance in the world’s 100 poorest countries, The MicroInsurance centre LLC. Retrieved on September 25, 2011 from http://www.microinsurancecentre.org/UploadDocuments/Landscape%20 study %20paper .pdf. Roth J and Mccord M J (2008) Agricultural microinsurance: global practices and prospects. Micro Insurance Centre, 1: 1-50. Roscuni B (2012) Savings in microinsurance: lessons from India, working paper 14, International Labour Office, Geneva. Roy P L and Holtz J (2011) Third party payment mechanisms in health microinsurance, working paper 13, International Labour Office, Geneva. Sahu B K (2010) Micro-insurance in India: outreach and efficacy , Centre for Microfinance Research (CMR), Lucknow. Retrieved on September 26, 2011 from http://www.birdi ndia.org.in/doc/Report%20on%20Microinsurance%20in%20India%20_Final.pdf. Srinivasan G and Arunachalam R S (2002) Micro insurance in India, International labour organisation. Retrieved on Feburary 11, 2012 from http://www.askmi.in/docs /Documentation %20on%20insurance/Microinsurance%20In%20India.pdf
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ANNEXURE Adoption of micro-insurance: an empirical study in Ludhiana city
Profile of Respondents Q 1 - Name of the respondent : __________ Contact Number if any :_________________ Q-2 Respondent Age? Up to 20 Years [ ] 50 to 60 Years [ ] 21 to 30 Years [ ] 60 and Above [ ] 30 to 40 Years [ ] 40 to 50 Years [ ]
Q 3 – Respondent Gender? Male [ ] Female [ ]
Q 4 – Marital Status ? Single [ ] Married [ ] Divorced [ ] Widow [ ] Q 5 – Highest Level of qualification attained? Primary School [ Diploma [ Yes [ ] ] No [ ] ] Secondary School [ ] Graduate [ ] Higher Secondary [ ]
Q 6 – Are you having a bank Account ?
Q 7 – Are you the main breadwinner in your household? Yes [ ] No [ ]
Q 8 – Current mode of employment? Self Employed [ ] Office Employed [ ]
Q 9 – Type of employment? Permanent [ ] Seasonal [ ] Contract Based [ ]
Q 10 - Respondent belongs to which Income group? 0 – 2500 Rs [ ] 2500 -5000 Rs [ ] 5000 -7500 Rs [ ] 7500 and above Rs [ ]
Q 11 – Different kinds of earnings which form part of your Income? Agriculture Income [ ] Sale of any goods [ ] Pension [ ] Formal employment [ ] Income received from government [ Any other __________________ ]
Q 12 – Do you save part of your income? Yes [ ] No [ ]
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Q 13 – What percentage of your Income is saved? 0-5% [ ] 6-10% [ ] 11-15% [ ] 16-20% [ ] 21 and above % [ ]
Q 14 – Kindly rank the various risks which you consider at while purchasing an insurance product. Highest risk according to you among these to be given 1st rank and then 2nd rank to the second greatest risk and so on. Kind of risk Poor Health Old Age Risk of life Property Risks Premature Death Any other Risk
AWARENESS QUESTIONS Q-15 Tick one of the following statements which you think represents the true meaning of insurance. Insurance Means Statements Investing money and getting return at later dates It is a form of risk-management which spreads risk of many people in exchange for payments from each Saving money with the instituion and getting interest on it Paying regular payment so you may get lump sum amount after few years Q 16 – Have you ever heard of Micro-insurance? Yes [ ] No [ ] Answer
Q-17 Tick one of the following statements which you think represent the true meaning of Micro- insurance. Micro-Insurance Means Statements Small saving schemes run by the government Protection of low -income people against specific perils in exchange for regular premium payments Special credit schemes run by the public institution for the poor people Insurance schemes for the short duration Q 18 - If any family member is having a micro-insurance product? Yes [ ] No [ ] Answer
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Q19- Tick in the column aware, if you are aware about that product and tick not aware column if you are not aware about that product ? Kind of insurance Life Insurance Health Insurance Livestock Insurance Asset Insurance Crop Insurance Aware Kind of insurance Life Insurance Health Insurance Livestock Insurance Asset Insurance Crop Insurance Not Aware
Q-20 Are you interested in buying micro insurance products? Yes [ ] No [ ]
Q-21 Write the Name of any Three Insurance Companies which at first comes to your mind. 1) __________________________ 2) ___________________________ 3) __________________________ Q-22 Please tick on the following insurance schemes run by the government for the poor people which you are aware of. MICRO-INSURANCE PRODUCTS OFFERED BY PUBLIC COMPANIES Life Insurance Products Janashree Bima Yojana [ ] LIC Jeevan Madhur [ ] Aam Aadmi Bima Yoajana [ ] Health Schemes Universal Health Insurance Scheme [ ] Gram Arogya Yojana[ ] Rashtriya swasth bima Yojana [ ] Wealth based crop insurance schemes Kissan Agriculture Pumpset Insurance [ ] National Agricultural Ins. Scheme Crop [ ] Livestock Insurance Cattle insurance by New India Assurance [ ] Cattle Insurance Policy by OIC [ ] Farm Income Insurance Scheme [ ] Farmers’s Package Policy [ ] Raja Rajeshwari Mahila Kalyan [ ] Janata Personal Accident Policy [ ] Krishi Shramik Samajik Suraksha [ ] LIC Jeevan Mangal [ ]
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Pension Schemes Varishtha Pension Bima Yojana [ ] MICRO-INSURANCE PRODUCTS BY PRIVATE COMANIES Life insurance Products Avia Amar Suraksha Life [ ] Kotak Gramin Bima Yojana [ ] Tata AIG Life Sampoorna Bima Yojana [ ] Tata Jana Suraksha Yojana [ ] Birla Sun Life Insurance Bima Suraksha Super [ ] Birla Sun Life Insurance Bima Dhan Sanchay [ ] Bajaj Allianz Sarve Shakti Suraksha [ ] Aviva Grameen Suraksha [ ] Tata AIG life sumangal yojna [ ] Tata AIG Navkalyan Yojana [ ] ING Surakshit Jivaan [ ] Super Suraksha [ ] Aviva Jana Suraksha [ ] ICICI Pru Sarv Jana Suraksha [ ]
Health Insurance Products Shakthi Security Shield [ ] Reliance Individual Mediclaim Insurance [ ] ICICI Advanced Medical Insurance [ ] Bajaj Allianz Critical Illness Insurance [ ] Assest or Possession insurance products ICICI Weather Insurance [ ] ICICI Tractor Insurance [ ] Reliance Agricultural Pumpset Insurance [ ] Live Stock Insurance Reliance Cattle Insurance [ ] ICICI Merchant insurance [ ] Rural Micro-Enterprise Shield [ ] Shakthi Health Scheme [ ]
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WILLINGNESS QUESTION Q-23 – Rate these fators from 1 to 5 showing your importance in buying micro-insurance products Tick the box which you want to represent your answer. FACTOR Extremely Very Imp Imp Important Less Imp Not at all Imp
Avialability of suitable product Premium Trust on the insurance companies Services provided by the insurance companies Awareness of product Premium Flexibilty Marketing by agents or company officials Income earned Age of the product buyer High Claim Reject Government support Flow of Income Refusal on the basis of health conditions Claim settlement procedure Documentation procedure Corporate image Claim ratio Word of mouth Recommendation of friends and relatives
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CONSTRAINTS QUESTION Q 24 – Kindly rate the importance of following constraints in the adoption of microinsurance. Rate the following constraints Variable Income Old Age Awareness of insurance Not able to save High Cost Low Income Non Flexibility of premium Non Availability of Suitable product Refusal by insurer to offer insurance schemes on health grounds Non accessibility due to Remote Area Lack of trust Never Felt for the need of insurance Extremely Very Imp Imp Important Less Imp Not at all Imp
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VITA
Name of the Student Father’s name Mother’s name Nationality Date of birth Permanent home address
Iqbal Singh Mr. Jasbir Singh Mrs. Kamaljeet Kaur Indian 5 October, 1988 H.No 10227, Street .No 7, Bhagwan chowk, Janta Nagar, Ludhiana 141003
EDUCATIONAL QUALIFICATION Bachelor degree University and year of award % marks Master’s degree OCPA Title of Master’s Project Report B.Com. Panjab University, Chandigarh, 2009 69.50 Master of Business Administration 7.02/10.00 Adoption of micro-insurance: an empirical study in Ludhiana city
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doc_301093364.pdf
In case you need this project this ask for it on email..i ll send u..
ADOPTION OF MICRO-INSURANCE: AN EMPIRICAL STUDY IN LUDHIANA CITY
Research Project Report
Submitted to the Punjab Agricultural University in partial fulfillment of the requirements for the degree of
MASTER OF BUSINESS ADMINISTRATION
in FINANCIAL MANAGEMENT
(Minor Subject: Economics)
By
Iqbal Singh (L-2010-BS-10-MBA)
Department of Business Management
College of Basic Sciences and Humanities
© PUNJAB AGRICULTURAL UNIVERSITY LUDHIANA - 141004
2012
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CERTIFICATE I
This is to certify that the research project report entitled, “Adoption of microinsurance: an empirical study in Ludhiana city” submitted for the degree of Master of Business Administration, in the subject of Financial Management (Minor subject: Economics) of the Punjab Agricultural University, Ludhiana, is a bonafide research work carried out by Iqbal singh (L-2010-BS-10-MBA) under my supervision and that no part of this research project report has been submitted for any other degree. The assistance and help received during the course of investigation have been fully acknowledged.
(Dr. Lalit Mohan Kathuria) Major Advisor Associate Professor Department of Business Management College of Basic Sciences and Humanities Punjab Agricultural University Ludhiana – 141004
ii
CERTIFICATE II
This is to certify that the project report entitled, “Adoption of micro-insurance: an empirical study in Ludhiana city” submitted by Iqbal Singh (L-2010-BS-10-MBA) to the Punjab Agricultural University, Ludhiana, in partial fulfillment of the requirements for the degree of Master of Business Administration, in the subject of Financial Management (Minor subject: Economics) has been approved by the external examiner along with internal examiner after an oral examination on the same.
_____________________ Internal Examiner
_____________________ External Examiner
_________________ (Dr. Sandeep Kapur) Head of the Department
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ACKNOWLEDGEMENT
The success of any project depends on the hard work and endeavour of not one but many, and this project is no exception. Acknowledging any one in mere words is a very difficult job. I would like to pay my sincere thanks to all those persons who helped me during this research project work with their able guidance and invaluable advice. It give me great pleasure in acknowledging the invaluable assistance extended to me by various personalities in the successful completion of this project report.. I express my heartfelt gratitude to my Major Advisor, Dr. Lalit Mohan Kathuria, Associate Professor, Department of Business Management, College of Basic Sciences and Humanities, for his dexterous guidance, inspiration, sustained encouragement, keen interest and precious time given to me during the course of research project and in successful completion of the manuscript. I express my deep appreciation to, Dr.Sukhpal Singh, Professor, Department of Economics and Sociology for his expert guidance. I owe my thanks to Dr. Sandeep Kapur, Professor-cum-Head, Department of Business Management and Dr. (Mrs.) Pratibha Goyal, Associate Professor, Department of Business Management for their valuable suggestions during the preparation of this manuscript. I express my sincere thanks to all other faculty members of Department of Business Management for providing necessary facilities during the tenure of my studies. Words at my command are inadequate to convey my sincere regards and respect to my loving parents and my family members for their deep affection, infinite encouragement and untiring moral support. Special thanks to my friends Varinder, Harsimran, Charu and Kanwarpal for their ever encouraging support, constant concern for my welfare and selfless sacrifices for my bright future.
Dated: Place: Ludhiana
__________________ (Iqbal Singh)
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Title of the Project Report study
:
Adoption of micro-insurance: an empirical in Ludhiana city
Name of the Student and Admission No. Major Subject Minor Subject Name and Designation of Major Advisor
:
Iqbal singh (L-2010-BS-10-MBA) Financial Management Economics Dr. Lalit Mohan Kathuria Associate Professor Department of Business Management Master of Business Administration 2012 51 + Annexure + Vita Punjab Agricultural University Ludhiana
: : :
Degree to be awarded Year of award of Degree Total pages in Project Report Name of University
: : : :
ABSTRACT India is a country with approximately 70 per cent of the population belonging to rural areas. The poor are more vulnerable to risks such as death, illness, injury and accident because of their economic circumstance. Approximately ninety percent are not covered by insurance. The present study was undertaken to find out the awareness regarding micro-insurance, analyze the factors influencing the willingness to adopt micro insurance and constraints in the adoption of micro insurance. To achieve these objectives, a sample, of 200 respondents was selected from Ludhiana city on the basis of convenience. The data were analyzed with statistical tools like mean score, Z-test, analysis of variance, and factor analysis. It was found that majority of the respondents were not aware about micro- insurance. Also, a small number of respondents had a micro-insurance policy. Life and health were most common forms of insurance undertaken by the respondents. The results highlighted that respondents consider ‘document and government support’, ‘income’, ‘trust and customer service’, ‘product awareness and availability’, ‘claim ratio’, and product flexibility’ as important factors influencing the adoption of micro-insurance. Respondents cited constraints like ‘trust on insurance companies’, ‘variable income’, ‘high cost ’, ‘awareness about the product’, ‘nonavailability of suitable product’, and ‘non flexibility of premium’ in the adoption of microinsurance product. Keywords: Micro-insurance, awareness, adoption, and constraints ______________________ Signature of Major Advisor ____________________ Signature of the Student
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CONTENTS
___________________________________________________________________________
Chapter
Topic
Page No.
_____________________________________________________________________
I. II. III. IV. V. INTRODUCTION REVIEW OF LITERATURE RESEARCH METHODOLGY RESULTS AND DISCUSSION SUMMARY REFERENCES ANNEXURES VITA 1-10 11-16 17-23 24-44 45-49 49-51
_____________________________________________________________________
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CHAPTER I INTRODUCTION Micro-insurance, the term used to refer to insurance to the low-income people, is different from insurance in general as it is a low value product (involving modest premium and benefit package) which requires different design and distribution strategies such as premium based on community risk rating (as opposed to individual risk rating), active involvement of an intermediate agency representing the target community and so forth. Insurance is fast emerging as an important strategy even for the low-income people engaged in wide variety of income generation activities, and who remain exposed to variety of risks mainly because of absence of cost-effective risk hedging instruments (Ahuja, 2005). India is a country of more than a billion people with more than 70 per cent of the population belonging to rural areas. In the past, government has attempted to provide various kinds of safety nets for the poor to cope up with unfortunate life events. However, the schemes or programmes are yet to cover a lot many poor. Insurance sector, where the total coverage is still 15 per cent as of now, in the life micro-insurance sector is estimated to have only at 2 per cent covering some 14 million adult lives. (Anonymous, 2010). Although the type of risks faced by the poor such as that of death, illness, injury and accident, are no different from those faced by others, they are more vulnerable to such risks because of their economic circumstance. In the context of health contingency, for example, a World Bank study reports that about one-fourth of hospitalized Indians fall below the poverty line as a result of their stay in hospitals (Ahuja, 2005). It was found that public ignorance is the widely rated as a significant barrier in the micro-insurance penetration. Very interestingly lack of probability of micro-insurance business is perceived not be a hindrance in the majority of the cases. Seventy seven countries out hundred were providing many efforts on availing access to insurance (Roth et al, 2007). Ninety per cent of the Indian population are not covered by insurance and signify an untapped market of nearly US $2 billion. This is a clear market failure, where the demand for microinsurance is not met by the supply of customized life and non-life insurance products. There is a clear role for the government here in linking micro-insurance to social protection schemes or exempting micro-insurance from the taxation applied to standard insurance products to encourage the provision of micro-insurance by commercial providers (Anonymous, 2007). The importance of insurance felt more when a poor family’s breadwinner dies, when a child in a disadvantaged household is hospitalized, or the home of a vulnerable family is destroyed by fire or natural disaster? Every serious illness, every accident and every natural disaster threatens the very existence of poor people and usually leads to deeper poverty. That’s where “micro-insurance” comes in (Anonymous, 2006). 1
1.1
History of Insurance sector in India The insurance sector has undergone many twists and turns over it’s 187 years of
operation, with a recent emphasis on growth and efficiency followed by an attempt to motivate rural and pro-poor focus. 1818 saw the advent of life insurance business in India with the establishment of the Oriental Life Insurance. General insurance business (nonlife) came into existence in 1850 with the commencement of the Triton Insurance Company. The first Insurance Act was formulated in the pre-independence period in 1938 (Anonymous,
2007). Regulated Indian insurers were divided into two core categories: life and general insurance. Life insurance includes products like endowment policies and retirement annuities. General insurance covers all other types of insurance. In 1956, the Indian Government nationalized the life insurance industry. The Government combined 154 insurance providers and formed the Life Insurance Corporation of India. The reasons given at the time were high levels of fraud in the industry and a desire to spread insurance more widely. General insurance remained in private hand until 1973 when it was nationalized (Anonymous, 2006). In 1999, the Insurance Regulatory and Development Authority (IRDA) was constituted as an autonomous body to regulate and develop the insurance industry. The IRDA was incorporated as a statutory body in April, 2000. The key objectives of the IRDA include promotion of competition so as to enhance customer satisfaction through increased consumer choice and lower premiums, while ensuring the financial security of the insurance market (Anonymous, 2012). The IRDA opened up the market in August 2000 with the invitation for application for registrations. Foreign companies were allowed ownership of up to 26 per cent. Today there are 24 general insurance companies including the ECGC and Agriculture Insurance Corporation of India and 23 life insurance companies operating in the country. The insurance sector is an already quite large and is growing at a speed of 15-20 per cent (Anonymous, 2012). 1.2 Meaning & Definition of Micro-insurance Micro-insurance is defined as “the protection of low-income people against specific perils in exchange for regular premium payments proportionate to the likelihood and cost of the risk involved”. Low-income people can use micro-insurance, where it is available, as one of several tools (specifically designed for this market in terms of premiums, terms, coverage, and delivery) to manage their risks” (Anonymous, 2006). Another definition highlights that micro-insurance is an insurance product that is targeted at low income households with a premium of less than Rs. 500 per annum and insured benefit of less than Rs 50,000 (Arvind, 2008). Micro-insurance has also been defined as an insurance that (i) operates by riskpooling (ii) financed through regular premiums and (iii) tailored to the poor who would otherwise not be able to take out insurance (Churchill , 2006 cited in Sahu, 2010). 2
Table 1 Type Of Cover (Rs) Life Insurance Health Insurance (Individual) Health Insurance (Family) Accident Benefit Table 2
Guideline for Life Insurers by IRDA Minimum Maximum Cover Cover 5000 5000 3000 30000 Min Term of cover 5 Years 1 Year Max Term of cover 15 Years 7 Years Min Age Entry 18 years Maximum Age Entry 60 Years
Insurer Discretion
10000 10000
30000 50000
1 Year 5 Years
7 Years 15 Years
Insurer Discretion 18 Years 60 Years
Source: Anonymous, 2008 Guidelines for Non Life Insurers by IRDA Min Cover 5000 Max Cover 3000 Minimum Term of cover 5 Years Maximum Term of cover 15 Years Min Age Entry 18 years Max Age Entry 60 Years
Type Of Cover (Rs) Livestock/Crop/ Asset Insurance Personal accident (per life/ earning member of Family
5000
30000
1 Year
7 Years
Insurer Discretion
Note: The minimum number of members comprising a group is at least twenty for group insurance. Source: Anonymous, 2008 At present, all insurance companies, both life and non-life in India are mandated by IRDA to do 20 per cent of their business from micro and rural insurance policies. In 2009-10, life insurers earned new business premium of Rs 4016.41 million from micro-insurance policies. Micro-insurance is not a profitable business segment for insurance companies because the premium generated is very low. For most insurance companies, distribution costs of micro-insurance products are often more than total premium earned ( Anonymous, 2012a). 1.3 Present Micro-insurance Scenario in India From a modest beginning, micro-insurance has been able to grow to a respectable size in the five-year period after issue of the IRDA Regulations. In the year 2010-11, the total premium collected under life and non-life micro-insurance portfolios put together was of the order of 15,430 million, out of which life insurance premium was 11,490 million and non-life insurance premium was 3,930 million (Anonymous, 2011). In 2010-11, 3.65 million microinsurance policies were sold in India in the year 2010-11 covering lives of 18.9 million people. The cumulative premium collected from micro-insurance was Rs.2.86 billion. Hence, micro-insurance constituted 4.59 per cent of the total lives covered, 7.6 per cent of total 3
number of policies and 0.23 per cent of premium collected by the insurance industry of India. With a premium collection of Rs.2.61 billion, the public insurer (LIC of India) is the market leader. (Mukerjee, 2012a). Table 3 Year 2007-08 2008-09 2009-10 2010-11 Source: Mukerjee, 2012 One third of the world’s poorest population are estimated to live in India. The World Bank estimates that 28 per cent of India’s population are living below the poverty line with more than 800 million people living in rural areas. In comparison with other countries, the micro-insurance market and distribution network in India are relatively well developed. In South America, Brazil appears to be the leading country with 56,00,000 insured persons and South Africa leads the African countries with 41,00,000 insured persons. Table 4 Country India Brazil South Africa China Indonesia Mexico Kenya Source: Coydon, 2011 1.4 Potential of Micro-insurance in Indian Context The potential market size for micro-insurance (life and non life) in India ranges between US $1,499 to 1,900 million approximately which is only expected to grow as microinsurance is better understood. In the case of life, the potential is estimated to be between US $350 to 500 million; in the case of non-life, between US $1,000 to 1,500 million approximately. The non-life estimation is limited to four types of coverage – (a) milch animals (b) livestock (c) health and (d) crop insurance. Some 52 percent of India’s population of 1.08 billion earns less than US $2 a day, of which one-third is estimated to earn less than US $1 a day. Micro-insurance can be an important constituent of a broader overall poverty Number of insured persons per country Insured persons per country 63,96,274 56,00,000 4,10,000 30,00,000 6,84,000 5,04,000 3,34,135 Number of micro-insurance policies sold for respective years Number of policies sold (in millions) 0.94 2.15 2.98 3.65
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reduction strategy to protect incomes and minimize loss of development gains among the low income populations (Anonymous, 2007). 1.5.1 Types of Micro-insurance Although there is no hard and fast rules describing the kinds of micro-insurance but according to prevalent micro-insurance products five categories could be made. With these five categories all the social and unadvantage group of people are tried to be covered (Anonymous, 2007). These are (a) Life micro-insurance (b) Health micro-insurance (c) Asset micro-insurance (d) Crop Insurance (e) Livestock or cattle Insurance 1.5.1 Micro-insurance schemes offered in India Following are the micro-insurance schemes offered by central government and public sector insurance companies in India. Janshree bima yojana This scheme was launched by the then Prime Minister Atal Bihari Vajpayee in 2000 as a group insurance scheme of LIC for the weaker sections of the society. The policy provides life, accidental and disability coverage to a group of people with minimum membership size of twenty five. This scheme provides benefits in the events of death (other than by accident) of the member, death/total permanent disability due to accident and permanent partial disability due to accident. It also provides the following coverage amount in case of Death of the member, an amount of Rs. 30,000, on death/total permanent disability due to accident, an amount of Rs. 75,000/?is payable. The premium under the scheme is Rs. 200/?per annum per member. Universal health insurance scheme is a community based insurance scheme was launched by the four public sector general insurance companies in July 2003. This scheme redesigned in 2004?05 made exclusively for persons and families below the poverty line with a premium of Rs. 165 for individuals, Rs. 248 for families of five persons and Rs. 330 for a family of seven. The benefits under the scheme were reimbursement of medical expenses up to Rs. 30000 towards hospitalization, an insurance cover for death due to accident to the amount of Rs. 25,000 and compensation due to loss of earning at the rate of Rs. 50 per day up to a maximum of 15 days. Varishtha Pension Yojana it is exclusively for unorganised sector workers of age 55 and above which is fully financed by the investment of the beneficiary with an annual return of 9 per cent in the form of monthly pension. The amount of pension benefit vary according to the amount invested from a minimum of Rs. 33,335 to a maximum of Rs. 2,66,665. The minimum and maximum monthly pension per month would be Rs. 250 and Rs. 2,000. The scheme is implemented by Life Insurance Corporation.
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Thrift fund scheme, “Under this scheme, every member is required to contribute 8 paise per rupee of wage earned and Central and State governments contribute 4 paise each to the fund”. The scheme is implemented by the Weavers Cooperative Societies/ Corporations. It provides temporary advance, partial and final withdrawal. New Insurance Scheme This scheme implemented by the United India Insurance Company and financed by the central government, state government and handloom weavers include payments in case of loss of dwelling due to natural calamities or fire, accidental death, reimbursement of hospitalisation charges and maternity benefits. Insurance for power loom weavers This scheme insures workers in the age group of 18 to 60 and with an income of Rs. 700 p.m. The central and the state government equally share the annual premium of Rs. 120. Benefits are given in case of natural death (Rs. 10,000) and accidental death (Rs. 20,000). In addition, the accumulated amount in the beneficiary’s running account earns an interest at 11 per cent per annum. National old age pension scheme It provides financial assistance of Rs 75 p.m. per beneficiary which has now been increased to Rs 200 p.m. to a destitute in the sense of having little or no regular means of subsistence from his/her own sources of income or through support of family members or other sources and whose age is more than 65. National family benefit scheme It targets households on the death of the primary breadwinner. The applicant should be of the age group of 18 to 65. A lump sum financial assistance of Rs. 10,000 is given. National maternity benefit scheme This is specifically targeted for pregnant women of 19 or more years belonging to households, upto first two live births. It gave a lump sum assistance of Rs. 500. The scheme was transferred to the Department of health and family welfare 19 with effect from 2000?01 from the Ministry of Rural Development. It has now been redesigned as Janani Suraksha Yojana in which cash benefits up to Rs. 1,300 in rural areas and Rs. 800 in urban areas to women in households for ante?natal care and institutional deliveries are provided. Jeevan Madhur It is a low premium endowment policy with accidental coverage. In this policy, if two full year premium has been paid, the cover will prevail for period of 2 years from the date of 1st unpaid premium. Minimum sum assured is Rs 5,000 while maximum is Rs 30,000. The age limit is from 18 years up to 60 years. Minimum premium is Rs 100 per month while maximum a person can pay is Rs 500 per month. Janata personal accident policy It covers any individual aged between 10 to 70. The sum insured is Rs.25, 000 to Rs.1,00,000 . Premium range is Rs.15 to Rs.240 per month risks covered accidents resulting in, death, permanent total disablement total and irrecoverable loss of use of limb loss of eye sight.
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Raj Rajeshwari Mahila Kalyan Yojna Policy this scheme provides economic security to women. All sections of women in the age group of 10 - 75 years irrespective of their income, vocation or occupation can be covered in this policy. Policy provides cover not only for the disablement of women but also for the death of her husband. Additional cover provides for temporary total disablement and also for loss damage to household goods. Benefits for Disablement of Insured women a) Permanent total disablement Rs.25,000 b) Loss of two limb/both eyes/one limb and one eye Rs.25,000 c) Loss of one limb/one eye Rs.12,500/. Premium is Rs15 per woman per annum or the basic cover and Rs.23 per woman per annum for both basic and additional cover (Anonymous 2010). Jeevan Mangal is a term assurance plan with return of premiums on maturity, where the premiums are required to be paid at regular intervals over the term of the policy. Persons 25 above the age of 18 years and upto the age of 60 years can participate in the scheme. The maximum maturity age is at 70 years. The term of the policy is 10 to 15 years with regular premium, however it is only 10 years for single premium. Also, the minimum and maximum sum assured are Rs. 10,000 and Rs. 50,000 respectively Following are some schemes offered by private sector insurance companies: Tata AIG’s Ayushman Yojana is a single premium plan where the policyholder pays the premium at the beginning of the policy term and gets the dual benefit of living as well as risk of death. This can be especially useful for those rural people who have a seasonal income. The policy is for the rural people falling in the age group of 18?60 years. The term of the policy is 10 years. AVIVA’s Jana Suraksha provides comprehensive financial protection to the children/dependants of the policy holder through low cost life insurance and guaranteed lump sum amount in case of death of the policyholder during the term of the policy. The term of the policy is for 5 or 10 years, subject to the maximum maturity age of 50 or 55 years respectively. The policyholders of age 18?45 years can participate in this and are required to pay the premium till the policy terms. The minimum life cover is Rs. 20,000 and the maximum is Rs 50,000. In the event of the death of the policyholder, the total sum assured is paid to the nominee. In case if the death occurred due to an accident, the life cover becomes the double. The maximum maturity age is 55 years. AVIVA’s Amar Suraksha is a protection plan that helps to secure the family’s future through a guaranteed lump sum amount in case of the death of the policyholder and with an option of minimum annual premium of Rs. 500. The term of the policy varies from 5 to 20 years with maximum maturity age at 50 years. The persons of age 18?45 years are eligible for thescheme. The premium paying term is same as policy term with minimum sum assured at Rs.20,000 and maximum at Rs 1,00,000. It covers both the living and death benefits. In case
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of death, the sum assured is paid to the nominee, while in case of maturity, the total premium paid is refunded back to the policyholder Birla sun life’s Bima Suraksha Super It provides life insurance cover on the payment of regular premium. The nominee gets the sum assured in the unfortunate event of death. This plan is simple and convenient with no medical tests and minimum documentation. A person aged 18 years can enter into the contract but the maximum entry age varies according to the term of the policy. Tata AIG’s Navkalyan Yojana Is a regular premium payment, low cost term plan for the rural adults who seek life insurance protection without any maturity benefit. It is five years term plan with age restrictions of 18 to 60 years AVIVA’s Grameen suraksha It is a term Insurance policy with total premium paid back on maturity. In this policy, only two yearly premiums are to be paid. This policy covers people up to the age of 55 Years only. This acts as a barrier in this policy (Anonymous 2012c). Insurance companies in India The number of insurance companies stood at 48 at the end of 2010-11, consisting of 23 life insurers, 24 non-life insurers and a reinsurer. Edelweiss Tokio Life Insurance Company was granted registration in the year 2011-12, leading to total number of insurance companies increasing to 49 as at end-September 2011. The Indian Insurance sector can basically be divided into two parts, one which is offering life insurance product others which include the rest. Then the sub categories could be formed in the form of public and private insurers. Public sector is still the dominant one when it comes to microinsurance specially offering the micro-insurance products to individuals. The only player in the life insurance category of public sector is still the LIC while the non life insurance sector now comprised of five companies. These are, National Insurance Company, New India Assurance Company, Oriental Insurance company, United Insurance Company, Agriculture Insurance Company. In total there are 20 insurers providing insurance in private sector 8 of them are non life insurers and 12 are life insurers. Birla Sun Insurance Company, HDFC standard life insurance company, ICICI prudential Life Insurance Company, Max New York Life insurance company, SBI life Insurance Company, TATA AIG life insurance company, AVIA life insurance company. 1.6. Classification of micro-insurance products India is home to many experiments in micro-insurance. Though officially there are 23 registered micro-insurance products filed by 15 insurance companies, there are a host of registered and non registered micro-insurance products in India. Micro-insurance products in India can be classified into four different types (Mukherjee, 2012). 8
Classification of Micro-insurance in India ? ? Products registered as micro-insurance products Rural and social products not registered as micro-insurance products Community based products in partnership with insurance companies; Independent community based micro-insurance products. Challenges in the way of Micro-insurance Although the micro-insurance has came a long since the micro-insurance regulations 2005 but the way for the micro-insurance has not been easy it has confronted many challenges in its way. The following issues play the key role of influencing the growth of the microinsurance industry in India, and coming as a hinder in the micro-insurance industry (Anonymous, 2012b).: 1. Difficulty in distribution is one of the most cited reasons for absence of rural insurance. The high costs of penetrating rural markets, combined with underutilization of available distribution channels, hinder the growth of rural insurance services. This adds to costs, both, managerial and financial. Like inclusive credit, inclusive insurance is expected to be a “low ticket” business, requiring volumes for viability. 2. Pricing, including willingness to pay and the availability of subsidies, influence the market. In the absence of a historical data base on claims, premium calculations are based on remote macro aggregates and overcautious margins. Building and sharing claims histories can help in aligning pricing decisions with actuarial calculations, thereby reducing prices. 3. Product design There is a mismatch between needs and standard products on offer. 4. Poor customization of product there is a low demand for what is available and insurance product developed. 5. The lack of insurance awareness is also seen as a challenge and translates into a relatively low demand for micro-insurance services. Commercial insurance companies, directly and through their partners, need to engage in the provision of insurance education. 6. Smaller premium is also a challenge since the amount of collected premium usually gets more than the marketing expenditure, acquisition cost of respondents as they are often living in remote areas and amount returned as claim. All these things add to high cost ratio for the companies. 7. There are specific reasons for low demand for insurance in spite of intense need. Suppliers have their own concerns which help to explain why there have been so little
?
? 1.7
9
efforts at market development. Consequently, the rural market is characterized by limited and inappropriate services, inadequate information and capacity gaps. 8. Cumbersome and inappropriate procedures inhibit the development of this sector. 9. The survey respondents state that the lack of available data, which is needed for risk assessment and premium calculations, is another significant challenge when entering this market. (Anonymous, 2012b). 1.8 Need for the present study India is the country currently having the most dynamic micro-insurance sector in the world. Liberalization of the economy and the insurance sector has created new opportunities for insurance to reach the vast majority of the poor, including those working in the informal sector. Even so, market penetration is largely driven by supply, not demand. Micro-insurance in India has valuable lessons for rest of the world, particularly in the regulation of the industry (Anonymous, 2006). Although the type of risks faced by the poor such as that of death, illness, injury and accident, are no different from those faced by others, they are more vulnerable to such risks because of their economic circumstance (Ahuja and Khasnobis, 2005). Microinsurance is specifically designed for the protection of low-income people, with affordable insurance products to help them cope with and recover from common risks. It is a market-based mechanism that promises to support sustainable livelihoods by empowering people to adapt and withstand stress (Anonymous, 2006) In the context of health contingency, for example, a World Bank study (Peters et al 2002), reports that 25 per cent hospitalized Indians fall below the poverty line as a result of their stay in hospitals. The same study reports that more than 40 per cent of hospitalized patients take loans or sell assets to pay for hospitalization (Ahuja and Khasnobis, 2005). There are some 14 million adults are covered by life micro-insurance in India. In a country with some 120 million families living on less than $2 a day, this is a very small proportion of the potential micro-insurance market and an indication of an untapped market of nearly US $2 billion. There is a need to understand the insurance requirements of low-income group, to study the awareness about micro-insurance, identify the factors affecting the willingness to adopt micro-insurance and identify the constraints in the adoption of micro-insurance.
So, the present study was aimed to achieve the following specific objectives: 1 To analyze the perception of respondents toward willingness to adopt microinsurance 2 To examine the constraints in the adoption of micro-insurance 10
CHAPTER II REVIEW OF LITERATURE An attempt has been made to present, in brief, a review of selected studies, which have a: direct or indirect relevance to this study. This is likely to provide a glimpse of work done on micro insurance. Aliber and Ido (2002) found that there was enormous scope for increasing the practice of microfinance institution based micro insurance, not just in terms of overall volume of business, but also in the variety of risks covered. Microfinance institutions can provide financial services, which provide insurance-like benefits. The regulatory framework needs amendment to accommodate micro insurance and there is a need for sensitization and education of prospective micro insurance claimants. Srinivasan and Arunachalam (2002) examined the demand for insurance from micro small enterprises and identified the details of microfinance institution activities concerning the (practical) operations for the provision of insurance services and also isolated difficulties they face. Ahuja and Jutting (2004) concluded a study based on community based micro insurance schemes and analyzes the how institutional rigidities that affect the demand for health insurance among the poor? Using a simple analytical model, the paper demonstrates that lack of demand for insurance need not necessarily be the result of affordability. Institutional rigidities, such as credit or borrowing constraints, may prevent low-income households from demanding insurance that they can otherwise afford. The paper also found that the absence of insurance can increase a poor household’s vulnerability, and push them into a poverty trap. For the poorest of the poor, affordability of insurance was still a major issue. Finally given these findings, the paper argued that the appropriate public intervention to generate demand for insurance may not be to subsidize premiums. Instead, the paper recommended that public intervention should remove institutional rigidities, for example, in labour, credit and product markets. Abels (2005) attempted to provide insights on the issues related to micro insurance and how micro insurance can be used to reduce the risk exposure of the low-income population. The note also provides a detailed analysis of the sector from the perspectives of clients, providers and supporting roles. Ahuja and Khasnobis (2005) observed that prospects of micro-insurance in India, and suggested strategies for its further extension. Analyzing the early evidence on micro 11
insurance, the paper also highlighted the current initiatives being contemplated to strengthen micro-insurance activity in the country. The authors study the developments on the supply side of micro insurance and observed that of the 80 listed insurance products, 45 cover only a single risk. Private insurance companies have more products than public companies. The available products cover a wide range of risks and most of the health insurance products exclude pregnancy related illness etc. The authors assessed the developments on the demand side of micro insurance and observed that 51 schemes are listed, with almost all being in the nascent stages. Nearly all insurance schemes are linked with micro financial services. Life and health are two most popular risks for which insurance is demanded. Barbin et al (2005) indicated that microfinance institutions have unique capabilities to cost-effectively delivery micro insurance to the informal sector. Micro insurance complements the microfinance institutions’ other interventions with medium scale enterprises because it reduces their vulnerability to business and personal risks. Just as microfinance has gained widespread acceptance as an effective development strategy; micro insurance, too, promises to be a sustainable approach to risk management for the informal sector. Microfinance institutions are currently in the best position to provide micro insurance to the informal sector and should actively experiment and innovate to make the mainstreaming of micro insurance a reality. Paul (2006) discussed the attempts to provide insurance against risks afflicting the poorest. It presents empirical evidence on the impact of different types of micro-insurance, and recommended the idea of ‘quasi-insurance’—the provision of insurance functions through a non-insurance route. The paper argues that micro-Insurance so far has been somewhat supply-driven rather than driven by effective demand, especially from the poorest, and thus the insurance products which would benefit the poorest are still at a limited stage of development. Institutional innovations and new insurance products therefore deserve promotion. Ramesh (2006) revealed health insurance schemes are increasingly recognised as preferable mechanisms to finance health care provision. In this direction micro health insurance schemes and community based health insurance schemes are assuming
significant importance in reaching large number of people. However, at the community level despite low premiums the penetration of health insurance is small. First determine the factors which affect the insurance purchase decisions. The results indicated that income and healthcare expenditure are significant determinants of health insurance purchase. Age, coverage of illnesses and knowledge about insurance were also found to be affecting health insurance purchase decision positively. For the decision regarding amount of health 12
insurance purchase, income was found to be having significant but non-linear relationship. In addition, number of children in the family, age, and perception regarding future healthcare expenditure were also found to be significant. Roth et al (2007) discussed the landscape of micro-insurance in the world’s poorest countries and found that public ignorance was the widely rated significant barrier in the highest public score in Togo, Burkina, Demonic Republic and Panama. 77 countries out of 100 countries under study were providing many efforts on availing access to insurance. Arvind and Renukumar (2008) observed that households (both microfinance institution clients and non-microfinance institution clients) had an access to and had taken regular insurance policies through the insurance agency network. Their associations with microfinance institutions showed well in their understanding and need for insurance. It was found that there was a strong need for endowment policies which the current micro insurance programmes fail to offer. At the microfinance institution level, though they understand the client needs well, they were not in a good position to carve out a suitable product for their clients. Insurance companies understand the basic issues in expanding into the rural sector like the necessity to associate with a trusted institution. But companies were still reluctant to design a suitable and an affordable group product that requires working closely with micro finance institutions and clients. Thus the study revealed the requirement for more education about micro Insurance at the mass level, the necessity for more bargaining power and insurance training at the microfinance institutions level and the need for a social perspective at the insurance company’s level. Dercon (2008) presented a selective overview of the current state of research on microinsurance. Its key purpose is to identify knowledge gaps that deserve further investigation. The study discussed the three core issues: the need for careful evaluation of the impact of microinsurance on the poor, the need to increase our understanding of the nature of the demand for microinsurance, including dimensions related to trust and the understanding of insurance by the poor, and finally, the need for further research on supply dimensions, focusing on the key challenges and bottlenecks for widespread and sustainable provision of microinsurance. Thankom and Susan (2008) analyzed the role of micro-insurance as an element of social protection. It outlined the current status of micro-insurance provision in Ghana and SriLanka, two countries with very different socio-cultural backgrounds. It concluded that both countries are unlikely to extend their social security systems to the entire population in the
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short to medium term, making private micro-insurance initiatives essential mechanisms to help people reduce their vulnerability. Brau et al (2009) analyzed that micro insurance institutions and instruments have developed rapidly over the last decade, with policies covering tens of millions in the base of the economic pyramid for markets in Africa, Asia, and Latin America. Ranging from simple policies providing life or health insurance to complex policies covering catastrophic risks for small landholders, it is a market with proven potential which demands closer attention. Cai et al (2010) observed the formal micro insurance in effect of economic development? the study results from a large randomized natural held experiment conducted in south-western China in the context of insurance for sows. The study found that providing access to formal insurance significantly increases farmers' tendency to raise sows and farmers are not previously efficiently insured through informal mechanisms. The study provided evidence to trust, or lack thereof, for government-sponsored insurance products was a significant barrier for farmers' willingness to participate in the formal insurance program, despite partial premium subsidy from the government. Hongbin et al (2009) revealed results from a large randomized natural field experiment conducted in south-western China in the context of insurance. The study assured two important questions about microinsurance. First, how does access to formal insurance affect farmers' production decisions? Second, what explains the low take up rate of formal insurance, despite substantial premium subsidy from the government? The study found that providing access to formal insurance significantly increased farmers' tendency to raise sows. We also provide several pieces of evidence suggesting that trust, or lack thereof, for government-sponsored insurance products is a significant barrier for farmers' willingness to participate in the insurance program. Mosley (2009) presented empirical evidence on the impact of different types of micro insurance, and recommends the idea of ‘quasi-insurance’—the provision of insurance functions through a non-insurance route—where institutional or regulatory constraints prevent insurance proper from being offered. The paper argues that micro insurance so far has been somewhat supply-driven rather than driven by effective demand, especially from the poorest, and thus the insurance products which would benefit the poorest are still at a limited stage of development. Institutional innovations and new insurance products therefore deserve promotion. Leatherman (2010) revealed the emergence of health microinsurance programmes worldwide provided hope to the poor. This study includes a literature review of 68 documents 14
covering the period from 1999 to 2010 and expert interviews with more than 31 experts representing 25 organizations. It focuses on private sector and discussed the challenges that limit the growth and impact. In addition to identifying barriers to success, the authors presented innovations that may move the field forward, including collaboration with public programmes. Matul (2010) fount that over 14 million low-income people in Africa who were covered by microinsurance at the end of 2008, almost double where this figure stood in 2004. Even with such growth, substantial parts of the continent remain almost barren of microinsurance. The paper concluded with a discussion of micro insurance challenges that must be overcome in order to facilitate broader, high-quality expansion in the years to come. Sahu (2010) examined micro-insurance programme in select areas and found that that the existing micro-insurance products were not demand driven in both high and low outreach areas. There was lack of understanding, awareness, extension services and development of insurance market that grossly affect wider use of insurance products and its uptake, particularly, among low-income sections of the society. Akotey and Gemegah (2011) revealed demand for micro- insurance in Ghana has found that premium flexibility, income level and nodal agency were significant determinants of micro-insurance demand. Insurance knowledge, expectation (trust) and marital status were also found to have positive and significant impact on the demand for micro insurance. Interestingly, the empirical analysis highlighted that formal education is not a significant determinant; rather one’s level of insurance knowledge had a positive and significant impact on micro-insurance demand. Bendig and Arun (2011) presented evidence on the determinants of insurance participation using probit models on household survey data from Sri Lanka, conditional on household’s microfinance institution enrolment. Further, the study employs multivariate probit regressions to analyze factors affecting the participation in different types of insurance. It was found that the household’s experience of a family related shock is positively associated with the participation in micro health insurance schemes under study. There was strong evidence that micro insurance has not yet succeeded in proportionately reaching the most vulnerable households. Notably, education of the household head was found to be a strong determinant of micro insurance participation. Heenkenda (2011) examined farmers’ willingness to pay for an Index Based Micro Insurance Scheme for paddy crops to protect against production loss caused by natural disasters in Sri Lanka and to assess product preferences for this IBMS. The contingent valuation 15
method was used to elicit the willingness to pay for the hypothetical IBMS. For product preferences, a conjoint analysis was conducted to study their relative importance and to discover the relationships between different attributes and the characteristics of the respondents. The results revealed that the interest in joining IBMS is 88 per cent overall. When willingness to pay is assessed, it is found that most potential purchasers would prefer a higher level than that offered by the existing conventional insurance plan. The results of the preference analyses demonstrated that for IBMS products can be adapted for specific locations in order to maintain demand. Matul et al (2011) presented results from the analysis of 15 micro-insurance schemes in Kenya, India and the Philippines using the international labour organisation's client value assessment tool called PACE (Product, Access, Cost and Experience). The PACE tool looked at the added value for clients from insurance products by comparing them to each other and to alternative means of offering protection from similar risks. The results presented that there is a place for micro-insurance to add value on the top of informal risk-sharing practices and existing social security schemes to protect low-income populations against life and health risks. The paper presented also a menu of interventions that can further improve client value from micro-insurance. Thankom A (2011) found that micro insurance was an emerging concept protecting households from the potentially catastrophic expenditures associated with family related shocks. The study presented evidence on the determinants of insurance participation using probit models on household survey data from Sri Lanka, conditional on household’s microfinance institution enrolment. Further, we employ multivariate probit regressions to analyse factors affecting the participation in different types of insurance. We find that the household’s experience of a family related shock is positively associated with the participation in micro health insurance schemes under study. There is strong evidence that micro insurance has not yet succeeded in proportionately reaching the most vulnerable households. Notably, education of the household head is a strong determinant of micro insurance participation. Roy and Holtz (2011) revealed health micro insurance schemes require that patients pay cash at the time of receiving health care services, and then seek reimbursement from the insurer at a later date. For low-income households, this could be a severe financial barrier. One common way to alleviate this barrier was to set up a third-party payment mechanism with selected health care providers. A third-party payment mechanism is a model for claims payment in which insured patients are not required to pay the entire cost of health services covered by the health micro-insurance scheme at the time the services are rendered. This 16
study on the experience of various health micro-insurance schemes and presented the pros and cons of using a third-party payment mechanism. Rusconi (2012) revealed products offered by Indian insurers that combine the benefits of insurance and saving. Combining these two financial instruments made sense when considering the complex financial lives of low income households. The study presented a framework that can be used to analyse the design of savings linked insurance products. The analysis highlighted the different approaches taken by the insurers, and provides preliminary insights for others interested in designing similar products. The review of above literature indicates that though few studies have been done conducted to check the awareness, and factors inducing low income people to purchase micro-insurance product, but there seems to be a lack of study analyzing the factors affecting the willingness to adopt micro-insurance and constraints in the adoption of micro-insurance. The present study is therefore an effort to fill the gap and to further the work already done in this field.
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CHAPTER III
RESEARCH METHODOLOGY
It is imperative to decide upon the research methodology well in advance to carry out the research in a most effective and systematic way. This chapter describes the research methodology adopted to serve the objectives of the study in an effective manner. This chapter consists of the five sections namely ‘conceptual framework’, ‘population and sample selection’, ‘collection of data’, ‘analysis of data’ and ‘limitations of the study’. These sections have been discussed below. 3.1 Conceptual framework The present study aims to examine the awareness of respondents towards insurance, micro insurance, micro-insurance schemes, to identify the various factors effecting the willingness to adopt micro-insurance. Also perception of respondents belonging to different income groups regarding constraints faced in the adoption of micro-insurance. For achieving the objectives primary data were used and the secondary information was also studied to find the relevant literature and statistics regarding micro insurance products and schemes run by government for the disadvantageous groups of India. For this study, respondents engaged in services as well as self-employed were selected for survey. Population for the study consisted of respondents of Ludhiana city. 3.2 Population and sample selection
The population of the study comprised respondents from both informal sector and formal sector. Formal sector mainly consisted of respondents providing services while informal sector mainly compromised of self employed. Individuals belonging to low income group comprised the major proportion of the sample; A sample of 200 respondents was selected on convenience basis and willingness of respondents to share information. 3.3 Collection of data To meet the objectives of the study primary data were collected through a predesigned, structured and non-disguised questionnaire. Before designing the questionnaire, a desk research was conducted to study the literature available on the subject. Various studies were reviewed to have a thorough understanding about various parameters to be included in questionnaire and accordingly a self-administered and structured questionnaire (as given in the Appendix) was designed to collect information from the respondents. Questions were specifically designed to get in-depth information about the profile of the respondents, awareness level of respondents towards insurance, kinds of insurance products, micro-insurance, and various micro-insurance schemes constraints faced in the adoption of micro-insurance. Questions related to factors influencing willingness to adopt 18
were also included. Both open ended as well as close ended questions were asked. Respondents were also asked scale based questions. For scale based questions, respondents were asked to provide their responses on a five-point Likert scale indicating their level of agreement, where ‘5’ showed ‘extremely important’, ‘4’ as ‘very important’, ‘3’ as ‘important’, ‘2’ as ‘less important’ and ‘1’ as ‘not at all important.’ The questionnaire was pre-tested and suitable modifications were incorporated before the final selection of the text of the questionnaire. Before filling the questionnaire, main objectives of the research were explained to the respondents. 3.4 Analysis of data The data collected through the questionnaire were converted to a master table which facilitated tabulation of data in desired form. The collected data were then grouped into tables and analyzed using various statistical tools like frequency distribution, percentage, mean score, standard deviation, Z-test, ?2 -test and factor analysis. To study the level of awareness among respondents, various questions regarding insurance, micro-insurance and various micro-insurance schemes were asked. A score of 1 was assigned to each question. Based on the scores, awareness level of respondents was grouped into 2 categories i.e. aware and not aware. Mean score was calculated for those questions, where respondents were asked to provide their responses on a 5-point Likert scale. The respondents were asked to indicate level of importance towards willingness to adopt micro-insurance and constraints faced in the adoption of micro-insurance. The weights given were as follows: 5 – Extremely Important 4 – Very important 3 - Important 2 – Less Important 1 – Not at all Important Mean score was calculated using the formula: Mean Score = (? Wi * Fn) / n i = 1 to 5 where Wi = weight attached Fn= associated frequency n = number of respondents If the mean score was more than mid point of the scale i.e. 3, it was concluded that respondents by and large tend to agree with the statement. Obtained mean score was tested against assumed mean of 3. For this, Z-test was applied and Z value was calculated to find out the statistical significance of each factor. The 19
formula used to calculate the z values is given below: Z=
( X ? µ) n S
X = calculated mean of the sample µ = assumed mean of the population i.e. 3 n = sample size S = standard deviation of the sample S=
?( X ? X ) 2 n ?1
Chi-square test (?2) was applied to test the statistical significance of the observed association between rows and columns of contingency tables. Chi-square was calculated by using the formula: ?2 = ? [(O-E)2 / E] Where O = Observed frequencies E = Expected frequencies And E = nr nc / n nr = total number in the row nc = total number in the column n = sample size Anova - one way an analysis of variance is a procedure used for comparing sample means to see if there is sufficient evidence to infer that the means of the corresponding populations distributions also differ. Analysis of variance is able to compare data for two or more distributions (George and Mallery, 2009). The analysis provided a test of the hypothesis that each sample is drawn from the same population against the alternative hypothesis that population is not the same for all samples. One-way classification was used. ANOVA was calculated using the following formula: Table 5 ANOVA Table : One-way classification model Sum of squares SSC SSE SST Degrees of freedom c-1 n-c n-1 Mean square Variance ratio of F MSC/MSE
Source of variation
Between samples Within samples Total
MSC=SSC/(c-1) MSE-SSE/(n-c)
20
Where, SST = Total sum of squares of variations SSC = Sum of squares between samples (columns) SSE = Sum of squares within samples (Rows) MSC = Mean sum of squares between samples MSE = Mean sum of squares within samples n = Total number of items c = Total number of columns Value of F was calculated at 5% level of significance The sum of squares total (SST) can be calculated as SS = ?X2 - CF where, CF =
??X ?2
N
and N is the total number of subjects The sum of squares between (SSB) can be calculated as : SSB =
2
T12 T22 T2 + + ...+ a -CF n1 n 2 na
2
where T1 is the total of the scores in group 1 squared, T2 is the total of the scores in group 2 squared, etc. n1 is the sample size for group 1, n2 is the sample size for group 2, etc. For the example data, With equal sample sizes, the formula for SSB can be simplified as:
SSB =
1 2 2 2 ( T1 + T2 +....+ Ta ) - CF n
To summarize the reasons influencing the willingness in the adoption of microinsurance. Factor analysis is a general name denoting a class of procedures used for data reduction and summarization. Factor analysis is based on the premise that in a research, there may be a large number of variables, most of which are correlated and which must be reduced to manageable level. Factor analysis is an interdependence technique that helps in determining underlying dimensions or factors that explain correlations among a set of 21
variables. Various statistics associated with factor analysis are: Factor: A factor is thus, simply a variable or construct that is not directly observable but needs to be inferred from the input variables.. Bartlett’s test of sphericity: It is a test statistic used to determine the hypothesis that variables are uncorrelated in the population implying that each variable has perfect correlation with itself but no correlation with other variables. Correlation matrix: A correlation matrix shows the simple correlations between all possible pairs of variables included in the analysis. Communality: Communality is the amount of variance a variable shares with all the other variables being considered. Eigenvalue: It represents total variance explained by each factor. Generally eigenvalues greater than 1 are used for each component. Factor loadings: These are simple correlations between the variables and the factors. Factor matrix: It contains the factor loadings of all the variables on all the factors extracted. Kaiser-Meyer-Olkin (K-M-O) measure of sampling adequacy: It is an index used to examine the appropriateness of factor analysis. Values between 0.5-1 indicate factor analysis is appropriate. For the present study, values of K-M-O measure came out to be greater than 0.5, so factor analysis was considered appropriate. Percentage of variance: This is the percentage of total variance attributed to each factor. Factor Rotation: The basic “un rotated” factor analysis usually employs principal component analysis. The objective of the principal component analysis is to determine minimum number of factors that will account for maximum variance in the data. Initial or unrotated results in factors that are difficult to interpret because the factors are correlated with many variables. So Rotation of factors can be undertaken so that factor matrix can be transformed into a simpler one that is easier to interpret. Generally varimax rotation is followed which minimizes the number of variables with high loadings on a factor, thereby enhancing interpretability of the factors. Interpretation: It is facilitated by identifying the variables that have large loadings on the same factor. That factor can be interpreted in terms of the variables that load high on it. Variables with factor loading greater than 0.5 are generally used for interpretation purposes. (Malhotra, 2008) Steps in conducting factor analysis: Coming to the analysis part, the analytical procedure systematically followed a series of steps to arrive at a solution. First of all, the objective of factor analysis was formulated. In the present study, factor analysis was applied on two questions. Objective of first question was to determine the factors which influence the willingness to adopt micro-insurance. Objective of second question was to ascertain the constraints in the adoption of micro-insurance. Then based on theory and judgement suitable 22
variables were included in the study and respondents were asked to indicate their level of agreement with the statements given to them (for both the questions) on a 5-point scale (5 = extremely important and 1 = not at all important). After that correlation matrix was constructed to see whether there were enough correlations to carry out factor analysis. Bartlett’s test of sphericity and K-M-O measure of sampling adequacy were also undertaken to judge the appropriateness of factor analysis. Preacher and MacCallum (2002) concluded that sample size depends on the level of communality of the variables and if all the communalities are above 0.6, smaller sample i.e. less than 100 may be perfectly adequate. Thus, the literature supports that sample size was adequate to carry out factor analysis. Once it was determined that factor analysis is appropriate for analyzing data, the data obtained were executed with factor analysis using principle component analysis utilizing varimax rotation method with Kaiser Normalization in order to reduce the information in many variables into a set of weighted linear combinations of those variables. In factor analysis, only those components were considered whose eigenvalue was greater than 1. Initially factor analysis was carried out on all the variables, but to get more reliable results, factor analysis was executed again by selecting only those variables from anti-image correlation matrix whose KM-O value was greater than 0.5. Interpretation was facilitated by analyzing table of rotated component matrix and total variance explained. All the factors were given appropriate names according to the variables that loaded on to each factor. Only variables with factor loading greater than 0.5 were considered for evaluation purpose. The factor analysis was executed with the help of SPSS software package. 3.5 Limitations of the study Following are the limitations of this study: 1. Due to time and resource constraints, respondents belonging to only Ludhiana city were considered for survey. A larger sample from different cities may be included in further studies. 2. Relationship between government supplier and willingness to purchase microinsurance may be studied in detail. 3. The information provided by respondents may not be fully accurate due to unavoidable biases.
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CHAPTER - IV RESULTS AND DISCUSSION This chapter presents the analysis of the primary data collected from the respondents. The study was conducted to understand and analyze the awareness and perception of respondents towards adoption of micro-insurance, and to find out the factors influencing the willingness to adopt micro-insurance. This chapter has been divided into four sections. The first section reveals the demographic profile of the respondents. The second section highlights the findings related to awareness among respondents regarding micro-insurance. The third section reveals the willingness of the respondents towards adoption of micro-insurance. The fourth section reveals the importance of constraints in the adoption of micro-insurance. 4.1 Profile of the respondents The profile of the respondents with respect to demographics like age, gender, qualification, marital status, occupation, family income, has been discussed in this section in detail. Table 6 Distribution of respondents on the basis of demographic Parameters (N=200) Demographic parameter Category Respondents n 18-20 years Age 21-30 years 31-40 years 41 and above Male Gender Female Primary School Secondary School Education Higher Secondary Diploma Graduate 65 34 34 70 18 44 32.50 17.00 17.00 35.00 9.00 22.00 22 129 30 19 135 %age 11.00 64.50 15.00 9.50 77.50
24
Unmarried Marital status Occupation Service Permanent Type of employment Seasonal Contract Based Rs 0-30,000 Rs 30,001-60000 Annual Income Rs 60001-90000 Rs 90001 and above Married Self Employed
126 74 62 138 138 33 29 13 74 80 33
63.00 37.00 31.00 69.00 69.00 16.50 14.50 6.50 37 40 16.50
The above table shows that a large majority of the respondents (75.5%) were in the age group of 18-30 year. Findings reveal that 77.5 per cent of the respondents were female, while the remaining 32.5 per cent were male. The result represents that 69 per cent of respondents studied up to higher secondary. It also depicts that 40 per cent of respondents were married while 73 per cent were unmarried. Self employed includes the persons like cart puller, rickshaw puller and an auto driver which are carrying out their business by limited means. The majority of the respondents (69%) were employed in services, 33 per cent of the respondents were self seasonally employed and rest 14.50 per cent were on contract based. The findings revealed that 56.5 per cent of the respondents had annual family income more than Rs 60,000. 4.1.1 Possessing a bank account The respondents were asked to indicate whether they have a bank account or not. Table 2 shows the distribution of respondents on the basis of having a bank account. Table 7 Distribution of respondents on the basis of possessing a bank account (N=200) Number of respondents 136 (68.00) 64 (32.00) 200 (100.00)
Having a Bank Account Yes No Total
Figures in parenthesis indicate percentage
25
The table 7 shows that majority of the respondents (68%) were having a bank account. while 32 per cent of the respondents did not possess a bank account. 4.1.2 Breadwinner of household Breadwinner is the one who has the major responsibility of running the house expenditure. The respondents were asked to indicate whether they are the breadwinner of the household will in the charge of running the house expenditure. Table 8 Distribution of respondents on the basis of being a breadwinner of Household (N=200) Breadwinner Yes No Total
Figures in parenthesis indicate percentage
Number of respondents 79 (39.50) 121 (60.50) 200 (100.00)
The above given table it is evident that majority of the respondents (69.50%) were not a bread winner. 4.1.4 Savings part of Income Table 9 shows the distribution of respondents on the basis of their savings. Respondents were asked to indicate whether they did save or not. Table 9 Savings Yes No Total
Figures in parenthesis indicate percentage
Distribution of respondents on the basis of Savings (N=200) Number of respondents 164 (82.00) 36 (18.00) 200 (100.00) The above given table below shows that larger majority of the respondents (82%) did
save. 4.1.5 Proportion of savings in income The respondents were asked to indicate what percentage of their income they save. Table 10 shows the distribution of respondents on the basis percentage of income saved.
26
Table 10
Distribution of respondents on the basis of percentage of savings (N=200)
Savings (%) 0-10% 11-20% 21 and above Total
Figures in parenthesis indicate percentage
Number of respondents 78 (39.00) 96 (48.00) 26 (13.00) 200 (100.00)
The above table reveals that larger majority of the respondents (48.00%) were saving between 11-20%, whereas 39 per cent respondents saved up to 10 per cent only. 13 per cent of the respondents were saving more than 21 per cent. 4.1.6 Risk considered while purchasing an insurance product Respondents were asked to rank in order of importance the various risks which were
considered while purchasing an insurance product. For analysis, weighted score has been calculated by multiplying the number of respondents with the rank given and thus summating the total scores. Rank 1 was then given to the risk having least summated score. The risk having second lowest summated score was given rank 2 and so on. Table 11 shows findings thus obtained. Table 11 Distribution of respondents on the basis of percentage of savings (N=200) S. No. Type of threat 1 2 3 4 5 Poor health Premature death Old age Property loss 36 31 24 11 Weighted score 2 65 40 23 28 3 31 58 41 36 4 44 19 44 78 5 24 52 68 47 Rank Weighted score 553 621 707 722 Rank 1st 2nd 3rd 4th
Figures in parenthesis indicate percentage The findings show that respondents rank poor health as the most important rish. Premature death, old age has been considered second and third most important risks respectively. 27
4.2
Level of awareness This section deals with awareness of respondents towards insurance, micro-insurance
and micro-insurance schemes. Respondents were also enquired about whether they have any micro-insurance product or not. Whether the respondents or any of the family members were having micro-insurance product was also asked. 4.2.1 Awareness towards insurance To study the level of awareness, respondents were presented with a set of statements regarding meaning of Insurance. Respondents were asked to pick the correct answers. Out of the statements, only one statement was correct. Results revealed that 51 per cent of the respondents were able to correctly answer the question regarding meaning of insurance. 4.2.2 Awareness towards micro-insurance Micro-insurance is the protection of low -income people against specific perils in exchange for regular premium payments proportionate to the likelihood and cost of the risk involved. Low-income people can use Micro-insurance, where it is available, as one of several tools (specifically designed for this market in terms of premiums, terms, coverage, and delivery) to manage their risks (Ahuja, 2005). To study the level of awareness, respondents were presented with a set of statements regarding meaning of Insurance. Respondents were asked to pick the correct answers. Out of the statements, only one statement was correct. Table 8 shows distribution of respondents on the basis of being aware of micro-insurance existence. Table 12 Distribution of respondents on the basis of being aware of microinsurance (N=200) Awareness regarding microinsurance Parameter Respondents n Awareness of microinsurance Aware Not aware Answered correct meaning of micro-insurance Yes No 84 116 74 126 %age 42.00 58.00 37.00 63.00
The above table indicates that majority of the person (58%) of the respondents were not ever aware about the existence of micro-insurance while 42 per cent of the respondents were aware that about the existence of micro-insurance. Results revealed that only 37 per cent of the respondents were able to correctly provide the meaning of micro-insurance while 28
majority of the respondents (73%) wrongly provided the meaning of insurance. 4.2.4 Possessing a micro-insurance product Table 13 shows distribution of respondents on the basis of possessing any microinsurance product. The table indicates that very large major share (83%) of the respondents were not possessing micro-insurance products. Table 13 Distribution of respondents on the basis of having a micro-insurance product (N=200) Having a micro-insurance product Yes No Total
Figures in parenthesis indicate percentage
Number of respondents 34 (17.00) 166 (83.00) 200 (100.00)
4.2.5
Awareness regarding various types of insurance Responses were further enquire about type of insurance they are aware about.
Table 14
Distribution of respondents on the basis of being aware about various types of insurance (N=200)
Types of insurance
Parameter
Respondents n %age 99.50 0.50 88.00 12.00 40.00 60.00 53.00 47.00 59.00 41.00
Life insurance
Aware Not aware Aware
199 1 176 24 80 120 106 94 118 82
Health insurance Not aware Aware Livestock insurance Not aware Aware Asset insurance Not aware Aware Crop insurance Not aware
The above table reveals that life insurance is most known insurance. A large majority of the respondents (99.5%) were aware of life insurance products. The table indicates that very a large proportion of the respondents (88%) were aware of health 29
insurance products. About fifty nine per cent of the respondents were aware of crop insurance .In case of asset insurance fifty three per cent of the respondents were aware of asset insurance. While the live stock insurance was the least known insurance only 40 per cent of the respondents were aware of livestock insurance. 4.2.6 Willingness to buy micro-insurance product Respondents were enquired about whether they were interested in buying microinsurance product. Table 15 shows distribution of respondents on the basis of willingness to buy micro-insurance. The table indicates that a large proportion of the respondents (69%) were interested in buying micro-insurance product. Table 15 Distribution of respondents on the Willingness to buy micro-insurance product (N=200) Willingness to buy micro-insurance product Yes No Total
Figures in parenthesis indicate percentage
Number of respondents 138 (69.00) 62 (31.00) 200 (100.00)
Chi-square test was applied to find out the association between age level of respondents and level of interest in buying micro-insurance products. The null hypothesis was there is no significant association between interested in buying micro-insurance and age of respondents. Results thus obtained are shown in table 15 Table 16 Distribution of respondents on the basis of age and interest in buying micro-insurance (N=200) Interested in buying Micro-insurance 18-20 years Yes No Total 15 (7.50) 7 (3.50) 22 (11.00) Age 21-30 Years 88 (44.00) 41 (21.50) 129 (64.50) 31-40 Years 21 (11.50) 9 (4.50) 30 (15.00) 41 and above 14 (7.00) 5 (2.50) 19 (9.50) Total 138 (69.00) 62 (31.00) 200 (100)
Figures in parenthesis indicate percentage Calculated chi-square value is .253 at 5 per cent level of significance Table value of chi-square is 7.81 d.f. = 3
30
The table 16 reveals that as observed chi-square value is less than table value of chisquare so it indicates that there was no significant association between age of respondents and interest in buying micro-insurance at 5 per cent level of significance. Table 17 Distribution of respondents on the basis of gender and interest in buying micro-insurance (N=200) Willingness to buy microinsurance product Yes No Total Gender Male 91 (45.50) 44 (22.00) Female 47 (23.50) 18 (9.00) Total 138 (69.00) 62 (31.00) 200 (100)
135 65 (67.50) (32.50) Figures in parenthesis indicate percentage Calculated chi-square value is .493 at 5 per cent level of significance Table value of chi-square is 3.84 d.f. = 1
The table 17 reveals that as observed chi-square value is less than table value of chisquare so it indicates that there was no significant association between gender of respondents and interest in buying micro-insurance of respondents at 5 per cent level of significance. Table 18 Distribution of respondents on the basis of education and interested in buying micro-insurance (N=200) Willingness to buy microinsurance product Yes Education Primary School 20 (10.0) 14 (7.00) 34 (17.00) Secondary School 25 (12.50) 9 (4.50) 34 (17.00) Higher Secondary 49 (24.50) 21 (10.50) 70 (35.00) Diploma 12 (6.00) 6 (3.00) 18 (9.00) Graduate 32 (16.00) 12 (6.00) 44 (22.00) Total 138 (69.00) 62 (31.00) 200 (100)
No
Total
Figures in parenthesis indicate percentage Calculated chi-square value is .253 at 5 per cent level of significance Table value of chi-square is 7.81 d.f. = 3
The table 18 reveals that as observed chi-square value is less than table value of chisquare so it indicates that there was no significant association between education of
31
respondents and interest in buying micro-insurance of respondents at 5 per cent level of significance. Table 19 Distribution of respondents on the basis of income and interest in buying micro-insurance (N=200) Willingness to buy micro-insurance product Yes Income 0-30000 10 (5.0) 3 (1.50) 13 (6.50) 30001-60000 46 (23.00) 28 (14.00) 64 (32.00) 60000-90000 60 (30.00) 20 (10.00) 80 (40.00) 90000 and above 22 (11.00) 11 (5.50) 33 (16.5) Total 138 (69.00) 62 (31.00) 200 (100)
No
Total
Figures in parenthesis indicate percentage Calculated chi-square value is 3.429 at 5 per cent level of significance Table value of chi-square is 7.81 d.f. = 3
The table 19 reveals that as observed chi-square value is less than table value of chisquare so it indicates that there was no significant association between income of respondents and interest in buying micro-insurance of respondents at 5 per cent level of significance. 4.2.7 Awareness towards insurance companies To study the level of awareness towards insurance company’s respondents were asked to name the three companies which at first come to their mind. Results revealed that 20 per cent of the respondents were not aware of any insurance company. One third of the respondents were aware of Life Insurance Corporation (LIC) of India. Next, twelve per cent of the respondents were aware of ICICI prudential life. While Bajaj, Birla and Aviva were the other private sector insurance companies which were known to respondents. 4.2.8 Awareness towards various micro-insurance schemes To study the level of awareness regarding micro-insurance schemes respondents were presented with a set of statements covering various schemes offered by public sector companies as well as private sector companies. Respondents were asked to mark the microinsurance schemes which they were aware of. Results revealed that majority of the respondents were not aware of even a single micro-insurance scheme. Micro-insurance schemes offered by public sector companies were more prevalent among respondents. Microinsurance schemes offered by LIC and health micro-insurance schemes were the schemes about which more consumers were aware.
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4.3
Parameters influencing the willingness to adopt micro-insurance This section presents analysis of finding regarding perceptions of respondents toward
parameters willingness to adopt the micro-insurance. Respondents were asked to give their response on a five-point Likert scale as ‘extremely important’, ‘more important’, ‘important’, ‘less important’ and ‘not all important.’ Table 20 S. No. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 Parameters influencing the willingness to adopt Micro-insurance Mean score 4.38 4.02 4.00 4.00 3.90 3.89 3.88 3.87 3.75 3.67 3.64 3.50 3.45 3.40 3.31 3.28 3.25 3.22 3.12 (N=200) Standard deviation 0.74 0.80 0.84 0.90 0.94 0.84 0.89 0.93 0.93 0.93 0.94 0.97 1.15 1.00 1.12 1.07 0.96 1.00 1.06
Parameters Trust on the insurance providers Premium Availability of suitable product Income earned Awareness of product Corporate image Services provided by the insurance companies Claim settlement procedure Flow of Income Claim Ratio Premium flexibility Documentation Government support Age of the insurer Word of mouth High claim rejection Refusal on the basis of health conditions Marketing by agents or company officials Recommendation of friends and relatives
Mean score analysis indicates that the major parameters that influence willingness to adopt micro-insurance were ‘trust on insurance companies (4.38)’, ‘income of the earner 33
(4.05)’, ‘availability of suitable product (4.05)’, ‘premium (3.90)’, ‘awareness of the product ( 3.88)’, ‘service provided by insurance companies (3.7)’, ‘non availability of suitable product (3.45)’, ‘non flexibility of premium (3.4)’,‘Old age (3.36)’ ‘non accessibility due to remote area (3.3)’ as important parameters influencing the adoption of micro-insurance. Mean score for majority of the statements was greater than 3 indicating that respondents by and large tend to agree with the statements. To identify the major factors influencing the willingness to adopt micro-insurance, factor analysis was performed. Further in order to test the suitability of data for factor analysis, reliability analysis was carried out with the help of Cronbach’s alpha, which is a measure of consistency. For this study, reliability coefficient (alpha) came out to be more than recommended lower limit of 0.7. Kaiser-Meyer-Olkin Measure of sampling adequacy and Bartlett’s test of sphericity favoured the appropriateness of factor analysis. K-M-O value for this study was 0.763. Bartlett’s test of sphericity was used to test the hypothesis that the variables were uncorrelated in the population. A large value of the test statistic (as shown in table 21) favoured the rejection of null hypothesis and showed that statistically significant number of correlations existed among the variables. The results have been presented in Table 21. Table 21 K-M-O and Bartlett’s Test of Sphericity 0.763 835.188 171 .000
Kaiser-Meyer-Olkin Measure of Sampling Adequacy Bartlett's Test of Sphericity Approx. Chi-Square df Sig.
Table 22 reveal the result that first factor named as Document and Government support, accounts for the largest proportion (11.933%) of total explained variance. Three variables like ‘documentation’, ‘refusal on the basis of health’ and ‘government support’ loaded on this factor. Factor 2 explained 11.624 of total explained variance and was named as ‘income’. Four items namely ‘income of the earner’, ‘friend recommendation’ ‘flow of income’ and ‘premium’ loaded on this factor. Factor 3 explained 10.031 of total variance and was named as ‘Trust and Customer service’. Three items namely ‘trust on insurance companies’, ‘service provided by insurance’, ‘claim settle procedure’ loaded on this factor. Factor 4 explained 10.038 of total variance and was named as ‘product availability and awareness’. Four items namely ‘age of the buyer’, ‘availability of suitable product’, ‘claim ratio’, ‘awareness of the product’ loaded on this factor.
34
Table 22
Rotated component matrix Factors
Parameters
DO and GS 0.802 0.601 0.546 0.44 0.023 0.22 0.144 -0.125 -0.037 0.122 0.305 -0.109 0.265 0.283 0.297 -0.079 0.024 -0.07 0.561 11.933 11.933
INC 0.107 0.012 0.076 0.261 0.769 0.659 0.649 0.545 0.128 -0.074 -0.126 0.208 0.39 0.287 -0.185 -0.104 0.155 -0.015 -0.011 11.624 23.557
TCS 0.069 -0.001 0.007 0.379 -0.128 0.173 -0.002 0.156 0.771 0.735 0.503 0.211 0.208 -0.027 0.275 0.051 0.341 -0.06 0.262 10.031 33.888
PAA -0.016 0.221 0.419 0.318 0.192 -0.176 0.149 0.208 -0.025 0.238 0.234 0.629 0.528 0.517 0.515 0.196 0.231 0.152 -0.12 10.038 43.936
Documentation Refusal on the basis of health Government support Marketing by agents or company officials Income earned Recommendation by friends or relatives Flow of the income Premium Trust on the insurance companies Service provided by the insurance companies Claim settlement procedure Availability of suitability product Awareness of the product Age of the product buyer Claim ratio High claim rejection Premium flexibility Word of mouth Corporate image Variation Explained (%) Cumulative variance explained (%)
CR and PF -0.003 0.416 -0.083 0.094 0.059 -0.354 0.216 0.32 -0.046 0.058 0.287 0 -0.148 0.171 -0.025 -0.709 0.546 0.034 -0.008 7.411 51.337
WM 0.074 -0.053 -0.199 0.071 -0.012 0.223 -0.177 0.015 -0.08 0.054 0.205 0.146 -0.1 0.015 0.336 0.022 0.123 0.852 0.561 7.296 58.637
Extraction Method: Principal Component Analysis. 6 Components extracted Marketing by company agents and High claim rejection ignored due to factor loading less than 0.5 DO and GS: Document and government support, INC: Income, TCS: Trust and customer service; PAA: Product awareness and availability, CR and PF: Claim ratio and product flexibility, WM: Word of mouth
35
4.4
Constraints in the adoption of micro-insurance This section presents the analysis of constraints faced by respondents in adopting the
micro-insurance. To analyze this, respondents were presented with a set of statements related to constraints and they were asked to give their response on a five-point Likert scale as ‘Extremely Important’, ‘More Important’, ‘Important’, ‘Less Important’ and ‘Not all Important.’ Table 23 S. No. 1 2 3 4 5 6 7 8 9 10 11 12 Constraints in the adoption of Micro-insurance (N=200) Statement Lack of trust Variable income High cost Awareness of product Not able to save Low income Non availability of suitable product Non flexibility of premium Non accessibility due to remote area Old age Refusal by insurer to offer insurance schemes on health grounds Never felt for the need of insurance Mean score 3.95 3.90 3.85 3.77 3.77 3.75 3.45 3.44 3.37 3.36 3.17 2.84 S.D. 1.05 .92 1.04 .96 .92 1.04 .97 1.01 1.10 1.09 1.01 1.20 Z-value 12.67* 13.79* 11.49* 11.37* 11.80* 10.17* 6.62* 6.12* 4.71* 4.65* 2.37* -1.87
*Significant at 5% level of significance (z-critical =1.96) From the above table, mean score analysis indicates that the major constraints in the adoption of micro-insurance were ‘lack of trust (3.95)’, ‘variable income (3.90)’, ‘High cost (3.85)’, ‘awareness about the product (3.78)’, ‘ not able to save (3.77)’, ‘low income of the respondent (3.7)’, ‘non availability of suitable product (3.45)’, ‘non flexibility of premium (3.4)’, ‘Old age (3.36)’, ‘non availability due to remote area (3.3). Mean score for majority of the statements was greater than 3 indicating that respondents by and large tend to agree with the statements. Z-test results were significant for all the parameters except the parameter ‘never felt the need for insurance, indicating that the observed mean value for the statement was significantly different from the assumed mean value of 3 at 5 per cent level of significance. Also the findings regarding differences in perception of respondents categorised on the basis of demographic variables (age, gender, education, income) towards constraints in the 36
adoption of micro-insurance have been presented below. Table 24 Differences in the perception of respondents categorised on the basis of age regarding constraints faced in the adoption of micro-insurance
Parameters Age category Up to 20 Variable income 21 -30 31-40 41 and above Up to 20 Old age 21 -30 31-40 41 and above Up to 20 Awareness of insurance 21 -30 31-40 41 and above Up to 20 21 -30 31-40 41 and above Up to 20 21 -30 31-40 41 and above Up to 20 Low income 21 -30 31-40 41 and above Up to 20 21 -30 31-40 41 and above Up to 20 Non availability of suitable product 21 -30 31-40 41 and above Up to 20 21 -30 31-40 41 and above N 22 129 30 19 22 129 30 19 22 129 30 19 22 129 30 19 22 129 30 19 22 129 30 19 22 129 30 19 22 129 30 19 22 129 30 19 Mean 3.86 3.93 3.90 3.73 3.72 3.17 3.86 3.42 4.00 3.69 3.80 4.00 3.86 3.68 4.00 3.89 3.86 3.69 4.13 4.42 3.90 3.62 4.00 4.05 3.22 3.48 3.56 3.15 3.59 3.41 3.53 3.42 2.86 3.17 3.46 3.05 S.D. 1.24 0.81 0.99 1.14 1.42 0.99 1.07 1.07 0.97 0.97 1.12 0.47 0.94 0.88 1.14 0.73 1.20 1.03 1.00 0.69 0.92 1.05 1.11 0.97 0.61 1.09 1.04 0.76 1.25 0.92 1.00 .90 0.56 0.98 1.38 0.84 0.27 0.844 1.86 0.136 1.02 0.381 4.50** 0.004 0.27 0.844 F Statistic p-value
Not able to save
1.20
0.309
High cost
3.68**
0.013
Non flexibility of premium
1.06
0.365
Refusal by insurer to offer insurance schemes on health grounds
1.62
0.184
37
Non accessibility due to remote area
Up to 20 21 -30 31-40 41 and above Up to 20 21 -30 31-40 41 and above
22 129 30 19 22 129 30 19
3.77 3.27 3.66 3.05 4.00 3.86 4.13 4.21
1.30 1.04 1.18 1.02 1.27 1.06 0.97 0.85
2.55***
0.057
Lack of trust
1.00
0.392
Up to 20 22 3.04 1.49 21 -30 129 2.94 1.16 Never felt for the need of 2.44*** insurance 31-40 30 2.60 1.19 41 and above 19 2.26 0.99 *Significant at 1 % level, **Significant at 5% level, ***Significant at 10% level
0.065
One-way ANOVA test was applied to all the parameters and the results are shown in the above table. Results reveal that significant differences has been found regarding perception of respondents categorised on the basis of age, towards constraints ‘high cost’, ‘old age’, ‘non- accessibility due to remote area’, and ‘never felt for the need of insurance’. Further, mean score analysis revealed that respondents above consider ‘high cost’ and ‘old age’ as a major constraint in the adoption of micro-insurance. While, respondents up to 20 years consider ‘non accessibility due to remote area’ as a major constraint. Table 25 Differences in the perception of respondents categorised on the basis of Gender regarding constraints faced in the adoption of micro-insurance Parameters Gender Male Variable income Female Male Old age Female Male Awareness of insurance Female Male Not able to save Female Male High cost Female Male Low income Female 38 N 135 65 135 65 135 65 135 65 135 65 135 65 Mean 3.82 4.06 3.13 3.83 3.74 3.83 3.68 3.93 3.77 4.00 3.76 3.73 S.D. 0.91 0.93 1.11 19.49* 0.87 1.05 0.32 0.74 0.97 0.78 1.07 0.96 1.13 0.85 1.99 .160 3.24*** .073 .571 .000 2.76 .098 F Statistic pvalue
0.02
.878
Male Non flexibility of premium Non availability of suitable product Female Male Female
135 65 135 65 135 65 135 65 135 65 135 65
3.30 3.72 3.43 3.49 3.11 3.27 3.24 3.63 4.02 3.80 2.88 2.75
1.06 7.73** 0.83 1.01 0.88 1.05 0.92 1.16 0.94 1.03 1.10 1.20 1.21 0.49 .484 1.93 .165 1.07 .301 0.14 .707 .006
Refusal by insurer to offer Male insurance schemes on health Female grounds Male Non accessibility due to remote area Lack of trust Female Male Female Up to 20 Never Felt need for insurance 21 -30
5.44**
.021
*Significant at 1 % level, **Significant at 5% level, ***Significant at 10% level
One-way ANOVA test was applied to all the parameters and the results are shown in the above table. Results reveal that significant differences has been found regarding perception of respondents categorised on the basis of a gender, towards constraints ‘not able to save’, ‘old age’, ‘non accessibility due to remote area’, and ‘non flexibility of the
premium’. Further, Mean score analysis revealed that female respondents consider ‘‘not able to save’, ‘old age’, ‘non accessibility due to remote area’, and ‘non flexibility of the premium’ as a major constraint in the adoption of micro-insurance. Table 26 Differences in the perception of respondents categorised on the basis of Education regarding constraints faced in the adoption of microinsurance Education Primary School Secondary School Variable Income Higher Secondary Diploma Graduate Primary School Secondary School Old Age Higher Secondary Diploma Graduate N 34 34 70 18 44 34 34 70 18 44 Mean 3.76 4.00 3.91 3.83 3.95 3.47 3.20 3.54 3.50 3.04 S.D. 1.12 0.95 0.95 0.70 0.77 1.23 1.14 0.98 1.09 1.05 1.75 0.140 0.33 0.851 F Statistic pvalue
Parameters
39
Primary School Secondary School Awareness of insurance Higher Secondary Diploma Graduate Primary School Secondary School Not able to save Higher Secondary Diploma Graduate Primary School Secondary School High Cost Higher Secondary Diploma Graduate Primary School Secondary School Low Income Higher Secondary Diploma Graduate Primary School Secondary School Non Flexibility of premium Higher Secondary Diploma Graduate Primary School Secondary School Non Availability of Suitable product Higher Secondary Diploma Graduate Primary School Refusal by insurer to offer insurance schemes on health grounds Secondary School Higher Secondary Diploma Graduate 40
34 34 70 18 44 34 34 70 18 44 34 34 70 18 44 34 34 70 18 44 34 34 70 18 44 34 34 70 18 44 34 34 70 18 44
3.97 3.91 3.72 3.72 3.61 3.67 4.02 3.67 3.77 3.79 4.08 4.17 3.90 3.22 3.59 4.29 4.02 3.50 3.22 3.75 3.32 3.26 3.52 3.44 3.52 3.38 3.44 3.54 3.55 3.34 3.20 3.00 3.31 3.22 3.02
0.75 0.62 1.12 1.07 0.99 0.94 0.90 0.91 0.80 0.97 1.05 0.86 0.98 0.94 1.16 0.87 0.90 0.94 1.26 1.14 0.94 0.79 1.07 1.04 1.13 0.98 0.82 1.03 0.92 1.01 0.84 1.04 1.00 0.80 1.19 0.84 0.497 0.38 0.817 0.56 0.688 5.47* 0.000 3.81** 0.005 0.96 0.427 0.88 0.476
Primary School Secondary School Non accessibility due to Remote Area Higher Secondary Diploma Graduate Primary School Secondary School Lack of trust Higher Secondary Diploma Graduate Primary School Never Felt need for the insurance Secondary School Higher Secondary Diploma Graduate
34 34 70 18 44 34 34 70 18 44 34 34 70 18 44
3.32 3.08 3.72 3.16 3.13 4.44 3.85 3.81 4.00 3.84 2.79 3.02 2.84 3.11 2.61
1.06 1.23 1.03 1.20 1.00 0.66 1.23 1.05 1.13 1.07 1.14 1.19 1.26 1.23 1.14 0.83 0.504 2.37*** 0.054 3.16* 0.015
*Significant at 1 % level, **Significant at 5% level, ***Significant at 10% level
One-way ANOVA test was applied to all the parameters and the results are shown in the above table. Results reveal that significant differences has been found regarding perception of respondents categorised on the basis of a education, towards constraints ‘high cost’, ‘low income’, ‘lack of trust’ and ‘non accessibility due to remote area’. Further, mean score analysis revealed that respondents having education up to primary school consider ‘low income’ as a major constraint. ‘Non accessibility due to remote area’ was major constraint for the respondents who have attained qualification up to higher secondary. Table 27 Difference in the perception of respondents categorised on the basis of Income regarding constraints faced in the adoption of micro-insurance Parameters Income category (Rs) 0-30,000 30,001-60000 60001-90000 90001 and above 0-30,000 30,001-60000 Old age 60001-90000 90001 and above 41 N 13 74 80 33 13 74 80 33 Mean 4.07 4.00 3.85 3.75 3.38 3.56 3.25 3.15 S.D. 0.75 0.93 0.90 1.03 0.96 1.12 1.09 1.03 1.57 0.197 0.77 0.508 F Statistic pvalue
Variable income
0-30,000 Awareness of insurance 30,001-60000 60001-90000 90001 and above
0-30,000 Not able to save 30,001-60000 60001-90000 90001 and above 0-30,000 High cost 30,001-60000 60001-90000 90001 and above 0-30,000 Low income 30,001-60000 60001-90000 90001 and above 0-30,000 Non flexibility of premium 30,001-60000 60001-90000 90001 and above 0-30,000 Non availability of suitable product 30,001-60000 60001-90000 90001 and above 0-30,000 Refusal by insurer to offer insurance schemes on health grounds 30,001-60000 60001-90000 90001 and above 0-30,000 Non accessibility due to Remote Area 30,001-60000 60001-90000 90001 and above 0-30,000 Lack of trust 30,001-60000 60001-90000 90001 and above
13 74 80 33
13 74 80 33 13 74 80 33 13 74 80 33 13 74 80 33 13 74 80 33 13 74 80 33 13 74 80 33 13 74 80 33
3.53 3.78 3.88 3.57
3.53 3.83 3.78 3.66 3.46 4.20 3.76 3.42 4.00 3.97 3.63 3.45 2.61 3.47 3.50 3.54 3.23 3.60 3.40 3.33 3.15 3.51 3.03 2.72 2.84 3.43 3.36 3.45 2.92 4.06 4.01 3.93
1.05 0.88 0.98 1.06
0.51 0.81 1.01 1.05 0.66 0.95 1.09 1.03 0.40 0.97 1.12 1.09 1.12 0.95 1.04 0.93 0.43 0.96 1.02 0.98 0.89 1.03 0.92 1.00 1.40 1.04 1.10 1.12 1.60 1.05 0.96 0.86 4.71** 0.003 1.11 0.345 5.78* 0.001 1.10 0.348 3.19** 0.025 2.59*** 0.053 5.81* 0.001 0.55 0.649
1.09
0.351
42
0-30,000 Rs Never felt need for the insurance 30,001-60000 Rs 60001-90000 Rs 90001 and above
13 74 80 33
2.84 2.50 3.05 3.09
1.34 1.25 1.10 1.15 3.36** 0.020
*Significant at 1 % level, **Significant at 5% level, ***Significant at 10% level
One-way ANOVA test was applied to all the parameters and the results are shown in the above table. Results reveal that significant differences has been found regarding perception of respondents categorised on the basis of income, towards constraints ‘high cost’, ‘low income’, ‘non flexibility of premium’, ‘lack of trust’, ‘refusal by insurer to offer insurance schemes on health grounds’ and ‘never felt for the need of insurance’. Further, Mean score analysis revealed that respondents having annual less than 60,000 per annum consider ‘high cost’, ‘low income’ and ‘lack of trust’ as a major constraint. ‘Non accessibility due to remote area’ was major constraint for the respondents earning more than Rs 90,000 per annum. 4.5 Discussions This section presents a discussion of the major findings revealed by the study. The first objective of the study was to determine the awareness among respondents towards microinsurance and factors influencing the willingness to adopt micro-insurance Results revealed poor health were considered most important risks while purchasing an insurance product resp. Larger majority (58%) of the respondents were not aware of micro-insurance. Most of the respondents (83%) were not possessing micro insurance products. Life insurance had most awareness among respondents followed by health insurance. 63 per cent respondents were interested in buying micro-insurance product. Life Insurance Company has got most awareness among respondents. Larger majority of the respondents were not aware of even a single micro-insurance scheme. ‘Trust on insurance companies’ and ‘income of the earner’ were two major factors which influence the willingness to adopt micro insurance. So companies should think twice and scrutinize each filed claimed very carefully before rejecting so as to build trust among people as ‘lack of trust’ has been considered major constraint in the adoption of micro-insurance. Second objective of the study was to study the various constraints in the adoption of micro-insurance. Results of the study revealed that respondents consider major constraints in the adoption of micro insurance were ‘lack of trust’, ‘variable income’, ‘high cost’ and awareness about the product’. It was found that there were significant differences in the perception of respondents categorized on the basis of income, towards constraints ‘high cost’, ‘low income’. Respondents having annual income less than Rs 60,000 per annum consider ‘high cost’, ‘low income’ and ‘lack of trust’ as a major constraint. Result indicated that
43
female respondents consider ‘not able to save’, ‘old age’, ‘on- accessibility due to remote area’, and ‘non-flexibility of the premium’ as major constraints in the adoption of micro insurance. Most of the respondents were willing to buy micro-insurance but due to constraints like ‘trust on insurance companies’ and ‘variable income’, ‘high cost ’, ‘awareness about the product’, ‘not able to save’ , ‘non- availability of suitable product’, and ‘non flexibility of premium’, they were not able to adopt micro-insurance products. So, suitable products, taking into account the low income levels prevalent in our country, should be developed should have enough flexibility regarding payments. Documentation should be kept as simple as possible for issuing a micro-insurance policy
44
CHAPTER - V
SUMMARY
In this chapter, a brief summary of the study has been presented, so as to understand the implications of the findings. The chapter also discusses recommendations and scope of the study. 5.1 Summary India is the country currently having the most dynamic micro-insurance sector in the world. Liberalization of the economy and the insurance sector has created new opportunities for insurance to reach the vast majority of the poor, including those working in the informal sector. Even so, market penetration is largely driven by supply, not demand (Anonymous, 2006). Although the type of risks faced by the poor such as that of death, illness, injury and accident, are no different from those faced by others, they are more vulnerable to such risks because of their economic circumstance (Ahuja and Khasnobis, 2005). Micro-insurance is specifically designed for the protection of low-income people, with affordable insurance products to help them cope with and recover from common risks. It is a market-based mechanism that promises to support sustainable livelihoods by empowering people to adapt and withstand stress (Anonymous, 2006). In the context of health contingency, for example, a World Bank study (Peters et al 2002), reports that 25 per cent hospitalized Indians fall below the poverty line as a result of their stay in hospitals. The same study reports that more than 40 per cent of hospitalized patients take loans or sell assets to pay for hospitalization (Ahuja and Khasnobis, 2005). There are some 14 million adults are covered by life micro-insurance in India. In a country with some 120 million families living on less than $2 a day, this is a very small proportion of the potential micro-insurance market and an indication of an untapped market of nearly US$2 billion (Anonymous, 2007). There is a need to study the awareness about micro-insurance, analyze the factors affecting the willingness to adopt micro-insurance and identify the constraints in the adoption of micro-insurance. So, the present study was aimed to achieve the following specific objectives: 1 To analyze the perception of respondents toward willingness to adopt microinsurance 2 To examine the constraints in the adoption of micro-insurance The population of the study comprised respondents from both informal and formal sector. Individuals belonging to low income group comprised the major proportion of the sample. A sample of 200 respondents was selected on convenience basis and willingness of respondents to share information. 45
To meet the objectives of the study primary data were collected. Primary data were collected through a pre-designed, structured and non-disguised questionnaire. Various studies were reviewed to have a thorough understanding about various parameters to be included in questionnaire and accordingly a self-administered and structured questionnaire was designed to collect information from the respondents. Questions were specifically designed to get in-depth information about the profile of the respondents, awareness level of respondents towards insurance, kinds of insurance products, micro-insurance, and various micro schemes constraints faced in the adoption of micro-insurance. Questions related to factors influencing willingness to adopt were also included. Both open ended as well as close ended questions were asked. Respondents were also asked multiple choices, dichotomous and scale based questions. For scale based questions, respondents were asked to provide their responses on a five-point Likert scale indicating their level of agreement, where ‘5’ showed ‘extremely important’, ‘4’ as ‘very important’, ‘3’ as ‘important’, ‘2’ as ‘less important’ and ‘1’ as ‘not at all important.’ 5.2 Findings of the study This section deals with findings and conclusions drawn from the study. 5.2.1 ? Awareness about micro-insurance among respondents Results revealed that risk of life and poor health were considered most important risks while purchasing an insurance product respectively. ? Results revealed that 51 per cent of the respondents were aware with the exact meaning of insurance while almost half share i.e. 49 per cent was not aware. ? Larger majority (58%) of the respondents were not aware of micro-insurance. Besides being aware of micro-insurance most of the respondents were not able to provide the exact meaning of micro-insurance. ? The results that that very large major share (83%) of the respondents were not possessing micro-insurance products, While only 17 per cent of the respondents were having any kind of micro-insurance products. ? Life insurance had most awareness among respondents followed by health insurance. The result indicates that very large proportion of the respondents (88%) was aware of health insurance products. ? Life Insurance Company has got most awareness among respondents followed by ICICI prudential life and Birla sun life. ? Larger majority of the respondents were not aware of even a single micro-insurance scheme. Life micro-insurance and health micro-insurance schemes were having more awareness among respondents then other kinds of insurance.
46
5.2.2 Factors influencing the willingness to adopt micro-insurance ? The results that large proportion of the respondents (69%) was interested in buying micro-insurance products. ? Results revealed that respondents consider ‘trust on insurance companies (4.38)’, ‘income of the earner (4.05)’, ‘availability of suitable product (4.05)’, ‘premium (3.90)’, ‘awareness of the product ( 3.88)’, ‘service provided by insurance companies (3.7)’, ‘non availability of suitable product (3.45)’, ‘non flexibility of premium (3.4)’,‘Old age (3.36)’ ‘non accessibility due to remote area (3.3)’ as important parameters influencing the adoption of micro-insurance. ? The factor analysis results highlighted that respondents consider ‘document and government support’, ‘income’, ‘trust and customer service’, ‘product awareness and availability’, ‘claim ratio and product flexibility’, ‘word of mouth’ as important factors influencing the adoption of micro-insurance 5.2.3 ? Constraints in the adoption of micro-insurance Results revealed that respondents consider major constraints in the adoption of microinsurance were ‘lack of trust (3.95)’, ‘variable income (3.90)’, ‘High cost (3.85)’, ‘awareness about the product (3.78)’, ‘ not able to save (3.77)’, ‘low income of the respondent (3.7)’, ‘non availability of suitable product (3.45)’, ‘non flexibility of premium (3.4)’, ‘Old age (3.36)’, ‘non availability due to remote area (3.3)’ ? Results reveal that there were significant differences in the perception of respondents categorized on the basis of age, towards constraints ‘high cost’, ‘old age’, ‘non accessibility due to remote area’, and ‘never felt for the need of insurance’. Further, mean score analysis revealed respondents above 20 years consider ‘high cost’ and ‘old age’ as major constraints in the adoption of micro-insurance. ? Also it was found that there were significant differences in the perception of respondents categorized on the basis of income, towards constraints ‘high cost’, ‘low income’, and ‘non flexibility of premium’. Further, Mean score analysis revealed that respondents having annual income less than Rs 60,000 per annum consider ‘high cost’, ‘low income’ and ‘lack of trust’ as a major constraint. ? Result indicated that female respondents consider ‘not able to save’, ‘old age’, ‘non- accessibility due to remote area’, and ‘non-flexibility of the premium’ as major constraints in the adoption of micro-insurance.
47
5.2.5
Conclusion
Thus the present study revealed that majority of the respondents was unaware about the micro-insurance and various micro-insurance schemes launched by government. Respondents consider ‘document and government support’, ‘income’, ‘trust and customer service’, ‘product awareness and availability’, ‘claim ratio and product flexibility’, ‘word of mouth’ as important factors influencing the adoption of micro-insurance. Most of the respondents were willing to buy micro-insurance but due to constraints like ‘trust on insurance companies’ and ‘variable income’, ‘high cost ’, ‘awareness about the product’, ‘not able to save’ , ‘nonavailability of suitable product’, and ‘non flexibility of premium’, they were not able to adopt micro-insurance products. 5.3 Recommendations of the study Majority of the respondents were not aware about the micro-insurance schemes launched by government, public sector and private sector companies. Therefore, steps need to be undertaken by government to create awareness among targeted people about the existing schemes so that benefits of the schemes reach in right hands. Awareness might be created by launching promotional programs on community radio, T.V etc. Also companies should think twice and scrutinize each filed claimed very carefully before rejecting so as to build trust among people as ‘lack of trust’ has been considered major constraint in the adoption of microinsurance. Also suitable products, taking into account the low income levels prevalent in our country, should be developed should have enough flexibility regarding payments. Documentation should be kept as simple as possible for issuing a micro-insurance policy. 5.4 Scope for future research A few areas where there is scope for further research are mentioned below: 1. Future studies may include larger samples from other cities. 2. Impact of government support and adoption of micro-insurance may be studied in future studies.
48
CHAPTER VI REFRENCES
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Anonymous (2011) Annual report 2010-11, Insurance Regulatory and Development Authority. Retrieved on March 20, 2012 from http://www.irda.gov.in/ADMINCMS /cms/frmGeneral_Layout.aspx?page=PageNo1583&flag=1&mid=Annual+reports+ %3e%3e+Annual+reports+of+the+Authority. Anonymous (2011a) Insurance in emerging markets: growth drivers and profitability, Swiss reinsurance company, economic research and consulting, Switzerland. Retrieved on March 5, 2012 from http://j7.agefi.fr/documents/liens/201112/21-liaoiblsgg8yhw6.pdf Anonymous (2012) History of insurance in India, Insurance Regulatory and Development Authority Retrieved on January 9, 2012 from http://www.irda.gov.in/ADMINCMS /cms/NormalData_L ayout.aspx?page=PageNo4&mid=2 Anonymous (2012a) Microinsurance, Retrieved on February 11, 2012 from http://www .banknetindia. com /finance/imicro.htm Anonymous (2012b) Micro insurance, Chapter 11. Retrieved on February 12, 2012 from http://www.nabard.org/pdf/report_financial/Chap_XI.pdf Anonymous (2012c) Compendium of Microinsurance Products, Retrieved on March 1, 2012 from http://www.srtt.org/institutional_grants/pdf/compendium.pdf Arun T and Steiner S (2008) Micro-Insurance in the context of social protection, working paper no. 55, Brooks World Poverty Institute, University of Manchester , Manchester. Banthia A, Johnson S, McCord M J and Mathews B (2009) Microinsurance that works for women: making gender-sensitive microinsurance programs, working paper 3, International Labour Office, Geneva. Bendig M and Arun T (2011) Enrolment in micro life and health insurance: Evidence from Sri Lanka, IZA Discussion Paper, 1-29. Bhat R and Jain N (2006) Factors effecting the demand for health insurance in a micro insurance scheme, working paper 2, Indian Institute of Management, Ahemdabad. Cai H, Chen Y, Fang H and Zhou L A (2009) Microinsurance, trust and economic development: evidence from a randomized natural field experiment, working paper 15396, National Bureau of Economic Research, Cambridge. Churchill C (2006) What is insurance for the poor? In Churchill, C. (ed.). Protecting the poor, A micro-insurance compendium, International Labour Organisation, Geneva. Coydon M A and Molitor A V (2011) Commercial insurer in microinsurance, Micro Insurance Network. Retrieved on March 5, 2012 from http://www.microinsurancene twork.org/publication/fichier/MiN_Commercial_insurers_study_2011.pdf Dercon S, Kirchberger M, Gunning J W and Platteau J P (2008) Literature review on microinsurance, working paper 1, International Labour Office, Geneva. Heenkanda S (2011) Prospective demand for an index-based micro insurance in Sri Lanka. Asia Pacific J Social Sci, 3: 1-31. Jim Roth and Michael J McCord (2008) Agricultural microinsurance global practices and prospects, The MicroInsurance Centre, United states of America. Leatherman S, Christensen L J and Holtz J (2010) Innovations and barriers in health microinsurance, working paper 12, International Labour Office, Geneva. 50
Matul M, Jaleran C T, and Kelly E (2011) Improving client value from microinsurance: Insights from India, Kenya, and the Philippines, working paper 12, International labour office, Geneva. Mausley P (2009) Assessing the success of microinsurance programmes in meeting the insurance needs of the poor, working Paper 84, University of Sheffield. Mittal N K (2009) Micro insurance, The institute of Chartered Accountants of India, New Delhi. Retrieved on January 15, 2012 from http://220.227.161.86/20959microinsur ance.pdf Morelli E, Onnis G A, Ammann W J and Sutter J (2010) Microinsurance an innovative tool for risk and disaster management, Global Risk Forum Davos, Italy. Mukherjee P (2012) Microinsurance product types in India, MicroSave India focus note 86. Retrieved on March 15, 2012 from http://www.microsave.org/sites/files/technical Briefs/indiaFocusNotes/IFN_86_Microinsurance_Product_Types_in_India.pdf Mukherjee P (2012a) Microinsurance in India: The Evolution of Market Trends, MicroSave India focus note 87. Retrieved on March 15, 2012 from http://www.microsave.org/sit es/files/technicalBriefs/indiaFocusNotes/IFN_87_MI_in_IndiaThe_Evolution_of_Ma rket_Trends.pdf Paul M (2009) Assessing the success of microinsurance programmes in meeting the insurance needs of the poor, DESA working Paper 84, Economics and social affairs. Peters D et al (2002). Better Health Systems for India’s Poor: Findings, Analysis, and Options,The World Bank, Washington DC. Rajeev Ahuja and Johannes Jütting (2004) Are the poor too poor to demand health insurance? J Microfin,6 Roth J, Mccord M J and Liber D (2007) The landscape of micro-insurance in the world’s 100 poorest countries, The MicroInsurance centre LLC. Retrieved on September 25, 2011 from http://www.microinsurancecentre.org/UploadDocuments/Landscape%20 study %20paper .pdf. Roth J and Mccord M J (2008) Agricultural microinsurance: global practices and prospects. Micro Insurance Centre, 1: 1-50. Roscuni B (2012) Savings in microinsurance: lessons from India, working paper 14, International Labour Office, Geneva. Roy P L and Holtz J (2011) Third party payment mechanisms in health microinsurance, working paper 13, International Labour Office, Geneva. Sahu B K (2010) Micro-insurance in India: outreach and efficacy , Centre for Microfinance Research (CMR), Lucknow. Retrieved on September 26, 2011 from http://www.birdi ndia.org.in/doc/Report%20on%20Microinsurance%20in%20India%20_Final.pdf. Srinivasan G and Arunachalam R S (2002) Micro insurance in India, International labour organisation. Retrieved on Feburary 11, 2012 from http://www.askmi.in/docs /Documentation %20on%20insurance/Microinsurance%20In%20India.pdf
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ANNEXURE Adoption of micro-insurance: an empirical study in Ludhiana city
Profile of Respondents Q 1 - Name of the respondent : __________ Contact Number if any :_________________ Q-2 Respondent Age? Up to 20 Years [ ] 50 to 60 Years [ ] 21 to 30 Years [ ] 60 and Above [ ] 30 to 40 Years [ ] 40 to 50 Years [ ]
Q 3 – Respondent Gender? Male [ ] Female [ ]
Q 4 – Marital Status ? Single [ ] Married [ ] Divorced [ ] Widow [ ] Q 5 – Highest Level of qualification attained? Primary School [ Diploma [ Yes [ ] ] No [ ] ] Secondary School [ ] Graduate [ ] Higher Secondary [ ]
Q 6 – Are you having a bank Account ?
Q 7 – Are you the main breadwinner in your household? Yes [ ] No [ ]
Q 8 – Current mode of employment? Self Employed [ ] Office Employed [ ]
Q 9 – Type of employment? Permanent [ ] Seasonal [ ] Contract Based [ ]
Q 10 - Respondent belongs to which Income group? 0 – 2500 Rs [ ] 2500 -5000 Rs [ ] 5000 -7500 Rs [ ] 7500 and above Rs [ ]
Q 11 – Different kinds of earnings which form part of your Income? Agriculture Income [ ] Sale of any goods [ ] Pension [ ] Formal employment [ ] Income received from government [ Any other __________________ ]
Q 12 – Do you save part of your income? Yes [ ] No [ ]
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Q 13 – What percentage of your Income is saved? 0-5% [ ] 6-10% [ ] 11-15% [ ] 16-20% [ ] 21 and above % [ ]
Q 14 – Kindly rank the various risks which you consider at while purchasing an insurance product. Highest risk according to you among these to be given 1st rank and then 2nd rank to the second greatest risk and so on. Kind of risk Poor Health Old Age Risk of life Property Risks Premature Death Any other Risk
AWARENESS QUESTIONS Q-15 Tick one of the following statements which you think represents the true meaning of insurance. Insurance Means Statements Investing money and getting return at later dates It is a form of risk-management which spreads risk of many people in exchange for payments from each Saving money with the instituion and getting interest on it Paying regular payment so you may get lump sum amount after few years Q 16 – Have you ever heard of Micro-insurance? Yes [ ] No [ ] Answer
Q-17 Tick one of the following statements which you think represent the true meaning of Micro- insurance. Micro-Insurance Means Statements Small saving schemes run by the government Protection of low -income people against specific perils in exchange for regular premium payments Special credit schemes run by the public institution for the poor people Insurance schemes for the short duration Q 18 - If any family member is having a micro-insurance product? Yes [ ] No [ ] Answer
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Q19- Tick in the column aware, if you are aware about that product and tick not aware column if you are not aware about that product ? Kind of insurance Life Insurance Health Insurance Livestock Insurance Asset Insurance Crop Insurance Aware Kind of insurance Life Insurance Health Insurance Livestock Insurance Asset Insurance Crop Insurance Not Aware
Q-20 Are you interested in buying micro insurance products? Yes [ ] No [ ]
Q-21 Write the Name of any Three Insurance Companies which at first comes to your mind. 1) __________________________ 2) ___________________________ 3) __________________________ Q-22 Please tick on the following insurance schemes run by the government for the poor people which you are aware of. MICRO-INSURANCE PRODUCTS OFFERED BY PUBLIC COMPANIES Life Insurance Products Janashree Bima Yojana [ ] LIC Jeevan Madhur [ ] Aam Aadmi Bima Yoajana [ ] Health Schemes Universal Health Insurance Scheme [ ] Gram Arogya Yojana[ ] Rashtriya swasth bima Yojana [ ] Wealth based crop insurance schemes Kissan Agriculture Pumpset Insurance [ ] National Agricultural Ins. Scheme Crop [ ] Livestock Insurance Cattle insurance by New India Assurance [ ] Cattle Insurance Policy by OIC [ ] Farm Income Insurance Scheme [ ] Farmers’s Package Policy [ ] Raja Rajeshwari Mahila Kalyan [ ] Janata Personal Accident Policy [ ] Krishi Shramik Samajik Suraksha [ ] LIC Jeevan Mangal [ ]
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Pension Schemes Varishtha Pension Bima Yojana [ ] MICRO-INSURANCE PRODUCTS BY PRIVATE COMANIES Life insurance Products Avia Amar Suraksha Life [ ] Kotak Gramin Bima Yojana [ ] Tata AIG Life Sampoorna Bima Yojana [ ] Tata Jana Suraksha Yojana [ ] Birla Sun Life Insurance Bima Suraksha Super [ ] Birla Sun Life Insurance Bima Dhan Sanchay [ ] Bajaj Allianz Sarve Shakti Suraksha [ ] Aviva Grameen Suraksha [ ] Tata AIG life sumangal yojna [ ] Tata AIG Navkalyan Yojana [ ] ING Surakshit Jivaan [ ] Super Suraksha [ ] Aviva Jana Suraksha [ ] ICICI Pru Sarv Jana Suraksha [ ]
Health Insurance Products Shakthi Security Shield [ ] Reliance Individual Mediclaim Insurance [ ] ICICI Advanced Medical Insurance [ ] Bajaj Allianz Critical Illness Insurance [ ] Assest or Possession insurance products ICICI Weather Insurance [ ] ICICI Tractor Insurance [ ] Reliance Agricultural Pumpset Insurance [ ] Live Stock Insurance Reliance Cattle Insurance [ ] ICICI Merchant insurance [ ] Rural Micro-Enterprise Shield [ ] Shakthi Health Scheme [ ]
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WILLINGNESS QUESTION Q-23 – Rate these fators from 1 to 5 showing your importance in buying micro-insurance products Tick the box which you want to represent your answer. FACTOR Extremely Very Imp Imp Important Less Imp Not at all Imp
Avialability of suitable product Premium Trust on the insurance companies Services provided by the insurance companies Awareness of product Premium Flexibilty Marketing by agents or company officials Income earned Age of the product buyer High Claim Reject Government support Flow of Income Refusal on the basis of health conditions Claim settlement procedure Documentation procedure Corporate image Claim ratio Word of mouth Recommendation of friends and relatives
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CONSTRAINTS QUESTION Q 24 – Kindly rate the importance of following constraints in the adoption of microinsurance. Rate the following constraints Variable Income Old Age Awareness of insurance Not able to save High Cost Low Income Non Flexibility of premium Non Availability of Suitable product Refusal by insurer to offer insurance schemes on health grounds Non accessibility due to Remote Area Lack of trust Never Felt for the need of insurance Extremely Very Imp Imp Important Less Imp Not at all Imp
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VITA
Name of the Student Father’s name Mother’s name Nationality Date of birth Permanent home address
Iqbal Singh Mr. Jasbir Singh Mrs. Kamaljeet Kaur Indian 5 October, 1988 H.No 10227, Street .No 7, Bhagwan chowk, Janta Nagar, Ludhiana 141003
EDUCATIONAL QUALIFICATION Bachelor degree University and year of award % marks Master’s degree OCPA Title of Master’s Project Report B.Com. Panjab University, Chandigarh, 2009 69.50 Master of Business Administration 7.02/10.00 Adoption of micro-insurance: an empirical study in Ludhiana city
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