Description
Design of Integrated Business Intelligence System Framework for Insurance Business Processes
International Journal of Applied Information Systems (IJAIS) – ISSN : 2249-0868
Foundation of Computer Science FCS, New York, USA
Volume3, No3., July 2012 – www.ijais.org
42
Design of Integrated Business Intelligence System
Framework for Insurance Business Processes
Dilbag Singh
Deptt. of Comp. Sc. & Applications
Ch. Devi Lal University, Sirsa (HR), India
Pradeep Kumar
Deptt. of Comp. Sc. & Applications
Ch. Devi Lal University, Sirsa (HR), India
ABSTRACT
Business intelligence is a key means to promote core
competence of enterprise. The high construction cost of
business intelligence severely limits the popularization
and development of business intelligence system.
Business process management (BPM) is a key business
initiative that enables companies to align strategic and
operational objectives with business activities in order to
fully manage performance through better informed
decision making and action. Effective business
performance requires an organization to model and
monitor not only its tactics but also its strategies and the
assumption on which these strategies are built. Decision
making is an important task for enterprise managers, and
is typically based on various data sources derived from
information systems, such as enterprise resource planning,
supply chain management and customer relationship
management. Numerous business intelligence tools (BI)
thus have been developed to support decision making.
Some existing BI tools have several limitations, for
example lacking data analysis and visualization
capabilities. The aim of this paper is to examine the
processes, methodologies and technologies underlying
BPM in insurance, the relation between BPM and
business intelligence, and to propose a framework for
integrating corporate performance management and
business intelligence.
Keywords
Insurance, business intelligence, business process,
framework
1 INTRODUCTION
In the past years, companies have understood the
importance of enforcing achievement of the goals defined
by their strategy through metrics-driven management.
Insurance organizations have vast technology assets to
assist them with day-to-day operations, regulatory
compliance, and financial reporting. Such systems record
transactions and manage operational processes, automate
compliance and controls, and roll up financial
performance data. To varying degrees, these systems
populate data warehouses (DW) that are exploited by
business intelligence (BI) systems. [1] The DW process,
though supporting bottom-up extraction of information
from data, fails in top-down enforcing the company
strategy.[2] The missing element, one that finance and IT
teams are now pursuing, is the integration of these
systems into a unified source of performance information
and analysis capability.
Early adopters of business process management have
focused on making the finance function more strategic –
mainly because people have tended to trust data coming
out of a financial system more than other corporate
systems, such as ERP or CRM. Almost every major
business function has a performance management element
that can be realized.[22] To enable this requires
organizations to put in place the right data platform and
source data and ensure that strategic thinking is driven by
the wider needs of the business. Organizations of all
shapes, sizes and markets are under pressure to conform to
increased regulatory compliance pressures and have a
need to link corporate performance to the decision-making
process. BPM can be the right answer in the same
direction.[23]
Now a days knowledge has become a key economic
resource [4] and been an important means to form the core
competence and obtain competitive advantage for all
kinds of enterprises. Knowledge is embedded in the
routine business data, such as consumption records of
customers, sales orders for dealers and supply voucher of
provider. To discovery the knowledge from those data
could effectively aid enterprises in scientific decision-
making and analysis.[5] Transforming the customer and
operational information into knowledge, Business
Intelligence (BI) provides the consolidation and analysis
of raw data, and the capacity of processing raw data into
the executable decision-making information. It could
enhance the competitiveness of enterprises by using
different sources from customers, operations and market
information [6].
The aim of this paper is to examine the processes,
methodologies and technologies underlying BPM in
insurance, the relation between BPM and business
intelligence, and to propose a framework for integrating
corporate performance management and business
intelligence. The proposed BI system can potentially be
considered as an efficient data analysis tool for supporting
business decisions.
International Journal of Applied Information Systems (IJAIS) – ISSN : 2249-0868
Foundation of Computer Science FCS, New York, USA
Volume3, No3., July 2012 – www.ijais.org
43
2. BUSINESS INTELLIGENCE
The various operational and transaction data can be
transformed into information and then knowledge by
using business intelligence (BI) tools. Enterprises decision
makers make better business decisions based on
systematic acquisition, collation, analysis, interpretation
and exploitation of information. BI components comprise
online analytical process (OLAP), knowledge
management, customer relationship management (CRM),
visualization, decision support system/executive
information system, data mining (DM) and geographic
information system (GIS) [11,15]. Wingyan et al. [6]
indicates that existing BI tools suffer several limitations,
such as poor data analysis and visualization capabilities.
Many advanced BI tools have been developed to
overcome weaknesses, including HP Openview
DecisionCenter [10] and Microsoft SQL Server 2008 [8].
Moreover, Michalewicz et al. [9] introduced a scheme of
an adaptive BI system, which combines optimization,
prediction and adaptability. The adaptive BI system is
capable of answering two questions:[16]
(1) ?What is likely to happen in the future??
(2) ?What is the best decision right now??
Li et al. [12] indicate that BI comprises concepts, methods
and process to improve business decisions, which employ
information from multiple sources, and use experience
and assumptions to develop an accurate understanding of
business dynamics. BI has several objectives [7]:
? to gather data from various sources;
? to transform this data into information and then
knowledge;
? to provide a friendly graphic interface to display
this knowledge.
Figure 1 illustrates the BI process, which works to
transform data into information, and then knowledge
using analytical tools, such as DM, OLAP, visualization
etc. Finally, the generated knowledge can be used to
support business decisions. BI systems have been used to
many application fields, such as ERP, SCM, CRM and
human resource management. [13]
Figure-1: BI Process
3. BI TECHNOLOGIES AND
BUSINESS PROCESSES
BI is composed of three core components, namely data
warehouse(DW), online analytical processing(OLAP)
and data miming(DM), where DW is the basis of BI
which provides comprehensible and accurate data
support for the other two components [14]. With the
development of global economic integration process,
enterprises in the world have broken through the national
border to carry out the manufacture, operation, and
service. Therefore, in construction of BI systems
enterprises need to consider the following [18]:
Distributed user circumstance: Global economic
integration makes various types of users in enterprise to
distribute in different area of the world. It needs BI
system to adapt to a distributed user circumstance.
Distributed data circumstance: Enterprises carry out
activities on a global scope which result in the global
distribution of business data. These data is the basis of
the formation of BI. Therefore it needs BI system to
adapt to a distributed data circumstance.
Heterogeneous data resources: The various business
processing systems of enterprise, such as ERP, CRM,
and SCM and so on, produce large amounts of business
data every day. These data is heterogeneous, redundant
and isolated each other. It needs BI system to integrate
heterogeneous data resources.
Organizations make choices and decisions based on the
quality of the information at their disposal. Data
warehousing can be the key factor for providing
management with the right information at the right time
to make solid choices, allowing key decision makers to
examine business trends and establish solid strategy for
the future.[17] Data Warehousing is believed to be a
competitive necessity. The management of knowledge
supports the competitive advantage of organizations.
Therefore, the effective use of data warehousing
(McManus and Snyder, 2003) to store knowledge can be
instrumental in supporting the competitive advantage of
companies. Considering the extensive size of the
database itself, the data warehouse is in a permanent state
of redesign in its model and structure. Having a massive
database is useless unless the relevant information is
retrieved quickly on request by the end user in real time
basis [20].
Productio
n Data
Internal
Data
External
Data
Archived
Data
Data
Staging
(ETL)
MDDB
Informatio
n
.
.
Data
Mining
OLAP
Report/
Query
Visualizat
ion
Knowledg
e
Decision
Data
Mart
Data
Warehous
e
International Journal of Applied Information Systems (IJAIS) – ISSN : 2249-0868
Foundation of Computer Science FCS, New York, USA
Volume3, No3., July 2012 – www.ijais.org
44
? Organizations need to have better and
enhanced business intelligence in reduced time
for the end users for efficient and effective
decision making.
? Consolidation of heterogeneous information
sources is a must for any firm to achieve
strategic advantage over competitors in the
market and market products and services at a
faster level.
? Replacement of older, less responsive decision
support systems is an important requirement to
reduce dependence on Information Systems
(IS) to generate reports.
The traditional implementation of BI is to extract data
from various business processing systems or local data
sources, transform and load data to DW at central site via
computer network. [19] Then DW-oriented analysis and
mining are carried out. It benefits scientific and effective
decision making of enterprise [21]. Oriented to the
current applied status, the traditional implementation
method requires enterprises to provide high-speed data
transmission networks, high-capacity data storage at
central site. It brings a heavy financial burden to
enterprises, especially to small and medium enterprises
which possess poor resource. To enhance scientific
decision-making and analytical capacity of the vast
number of domestic traditional enterprises and small and
medium enterprises in international competitiveness, this
paper takes the advantages of multi-agent technology to
give a low-cost BI systems design which can reduce the
construction cost of BI system and extend the applied
scope of BI by minimizing the amount of data transfer
and data storage. [24, 25]
Any BI implementation is aimed at turning available data
into information and delivering it to the decision makers.
BPM is focused on a subset of the information delivered
by a BI system – the information that shows business
performance and indicates business success or failure
and enables organizations to focus on optimizing
business performance. [22]
BPM involves a closed-loop set of processes that link
strategy to execution in order to respond to that task.
Optimum performance is achieved by:
? Setting goals and objectives – strategize
? Establishing initiatives and plans to achieve
these goals –plan
? Monitoring actual performance against the
goals and objectives – monitor
? Taking corrective action – act and adjust
The key to effective BPM is tying performance metrics
to business strategy, and that means a melding of two
areas of technological functionality: strategic
management systems and performance metrics.
The first are systems that manage the key business
processes that affect strategy execution, including
objective management, initiative management, resource
management, risk management and incentive
management.
The second is essentially a business intelligence platform
for automated data exchange, reporting and analysis.
BPM should produce three core deliverables: [23]
? Information delivery to enable managers to
understand the business.
? Performance oversight to enable them to
manage the business.
? Performance effectiveness to enable them to
improve the business.
Business performance management must be an
enterprise-wide strategy that seeks to prevent
organizations from optimizing local business at the
expense of overall corporate performance.
Business Information Technologies are seen as cutting
edge Information Technologies made on purpose to
support business information engineering. Management
methods, techniques and support tools could be seamless
integrated with Business Intelligence components in
special tailored or customized Performances
management systems. The main functions of these
systems are:
? To gather and store different measures of the
business on a regular basis (current state
indicators of the business performances).
? To gather and store benchmarks and targets
(threshold values) and business rules
(interpretations of comparison results between
current performance’s indicators and etalon
values).
? To facilitate roll-ups and drill-downs of
analyzed indicators along hierarchical
aggregation criteria (structured Performance
Measurements).
? To keep the ongoing analysis alert - allowing
decision makers to quickly evaluate which
business processes are successful, and which
need their attention.
To summarize, an effective Business Performance
Information System is built and maintained by business
users to support the decision-making process especially
at strategic level, making use of various indicators –
quantitative and qualitative, lagging and leading –
balanced against targeted objectives and/or industry
benchmarks. Lastly, with performance measurement
periods becoming shorter, management must have the
capability to more proactively influence the outcome.
That requires monitoring and tracking capabilities that
can generate current, complete and accurate information
upon which they can act in real time. Business
information technologies must respond to that need of
proactively managing business performance.
4. BI AND INSURANCE BUSINESS
PROCESS MANAGEMENT
Business intelligence can be considered as being the final
component of business process management (BPM) after
the decision support systems, enterprise information
International Journal of Applied Information Systems (IJAIS) – ISSN : 2249-0868
Foundation of Computer Science FCS, New York, USA
Volume3, No3., July 2012 – www.ijais.org
45
systems. If BPM is an outgrowth of BI and incorporates
many of its technologies, applications and techniques,
than why BI itself can’t deliver the insight needed to
improve overall business performance? From a
theoretical viewpoint, it can. From a practical standpoint,
it hasn’t. Like decision support; BPM is more than a
technology. It involves the processes, methodologies,
metrics and technology used to monitor, measure sand
manage a business. Once selected the business process
that has to be improved, and the business methodology to
be implemented, there are the metrics (to monitor,
measure and change) to be established. These metrics
(key performance indicators) are defined and selected by
the business and not by the IT. The final step is to choose
the business performance measurement technology. We
can say that business intelligence it is just business
measurement and not business performance
management. BPM is not a single technology, but rather
a combination of elements – BI, score carding, profiling.
BI looks at and analyses the past and what has happened
up until today – this is useful, as planning requires
knowledge and you can set planning goals based on the
past. Score carding enables you measure how you are
performing against those planned goals. Every
organization has processes in place that feed back to the
overall plan. [26]
What’s new with BPM is the integration of these
processes, methodologies, metrics and systems – an
enterprise wide strategy that seeks to prevent
organizations from optimizing local business at the
expense of overall corporate performance.
The industry is looking to improve its performance in
various areas: improved quality of underwriting, multiple
options of premium payment, enhanced claims
management processes, easy way of renewal,
discontinuation of policy , better management of the
exposure/risks created from declining investment returns
and the development of better business controls and
reporting, both operationally and financially[26]. Apart
from these core areas, insurers are looking at increasing
channels of distribution, which affects the profitability of
their business, through alliances. The various areas of
this sector in which business intelligence is required are
[27]:
Sales and Marketing: Analyse customer behaviour and
buying patterns to create new products and services that
help sales teams to meet revenue goals. Identification of
cross selling/ upselling opportunities involves
identification of those customers in the existing database
whose likelihood of responding to a product which they
do not hold presently is the highest.
Claim Fraud Detection & Prediction: Identify
fraudulent patterns and use historical data to uncover past
fraud cases. Improve cost saving with more efficient and
effective fraud detection. The analytic solutions which
help manage the complex claims process effectively and
help detect fraud by accurately forecasting likely
outcomes in order to mitigate the severity of the claim.
Customer Segmentation/Classification: It is extremely
important for insurer to segment customer based on their
behavior and potential profitability. Analytics can help
them more accurately, which policies and services to
offer to which customers. Apart from customer
segmentation, data mining can also be used to predict the
likelihood of policy cancellation in advance.
Market/Product Analysis: As there are several products
to cater the need of various customers. Which product is
suitable for the customer demographics? Planning and
launching of new product for the targeted customers.
Risk Management: To adapt a risk based approach,
insurers will have to implement an economic capital
regime, where they predict and evaluate the risk profile
of the underwritten business under both best case and
worst case scenarios. Simulation techniques and
stochastic model for various risk such as credit market
liability; underwriting and operational risk can be used
for scenario and stress testing to determine the optimum
economic capital level.
5. DESIGN OF INTEGRATED BI
FRAMEWORK FOR INSURANCE
The integration of business and IT process management
and BI is a key enabler for BPM. It provides the ability
to effectively manage the business and achieving
business goals.
The BPM framework presented below is based on the
integration of business and IT processes at all decision
levels (strategic, tactical and operational).
In the figure-2, the various BI users are Market Product
Research, Business development, Insurance consultant,
Customer service, Management /DSS. Outside Databases
includes data that are acquired from external
market/industry research and multiple insurers in
different formats. Company/product Databases includes
insurance company/product analysis information,
Product terms, fee rate, company analysis/rating
information, etc. Operation Databases includes various
kinds of operation information such as customer
information (customer purchased product, buying
behaviour, customer service), sales information (sales
performance, productivity, activity management), etc.
A set of powerful Data Warehouse applications are built
based on this infrastructure. Multiple well-established
databases provide the following services to Data
Warehouse users:
? CRM services (for Business Development
and Customer Service Dept.) - in-depth
analysis of customer value, needs, buying
behavior, service requirements, etc. are
provided to support more effective and targeted
customer development and customer services.
? Sales management services (for Sales Mgmt
Dept.) - in-depth analysis of sales team
productivity and performance are provided to
support tailored management, training and
coaching efforts.
? Market/product analysis services (for
Research Dept.) - accumulated product sales
data and market research data are used as input
to adjust product-selecting approach and guide
strategic direction of future development.
International Journal of Applied Information Systems (IJAIS) – ISSN : 2249-0868
Foundation of Computer Science FCS, New York, USA
Volume3, No3., July 2012 – www.ijais.org
46
Figure-2: Integrated BI framework for insurance
? Management and decision supporting services
(for Management) - management/ operation
performance tracking analysis are provided based
on integrated OLAP (Online Analytical Processing),
data mining technologies to support key
management decisions to ensure market
competitiveness.
Business intelligence is a business management term, which
refers to applications and technologies that are used to gather,
provide access to, and analyze data and information about
company operations. Business intelligence systems can help
companies have a more comprehensive knowledge of the
factors affecting their business, such as metrics on sales,
production, internal operations, and they can help companies
to make better business decisions.
Business flexibility and agility require continuous monitoring
of the business processes and support of an appropriate BI
environment. An environment that provides information
sufficiently current (near real time) to support the
requirements for both operational and strategic decision
making. BI technologies and products are evolving in order to
provide such an environment, and we can list only some of the
new trends:
? linking business process data to operational activity
data for a complete for a complete view of the
enterprise;
? implementation of business rules and Key
Performance Indicators to enable consistent
management of the business activities;
Data Warehouse
MDDB
Data Mart
Meta Data
Outside data source
Company Database Other data source
Underwriting/Pre
mium Payment
Claim
Surrender
Partial Return /
Maturity Return
BI User 1
BI User 2
BI User 3
BI User n
OLAP / Data
Mining
Information
Subject 1
(Sales &
Marketing)
((
Information
Subject 2
(Fraud
Detection)
Information Subject
3
(Cust Classification
& Prediction)
Information
Subject n
(Risk
Management)
Information
Subject 4
(Mkt/Product
Analysis)
International Journal of Applied Information Systems (IJAIS) – ISSN : 2249-0868
Foundation of Computer Science FCS, New York, USA
Volume3, No3., July 2012 – www.ijais.org
47
? automatic alert generation for proactive problem
avoidance rather than reactive problem impact
minimization;
? real time data flow to enable monitoring and
proactive management of business processes.
A BI environment that include these capabilities enables
companies to proactively manage their businesses, rather than
just react and adjust to business situations as they arise. The
main objective of BPM is to help companies improve and
optimize their operations across all aspects of their business.
But implementing BPM is much more than just about
choosing new technology – it suppose a constant analyze of
business environment to determine if changes are required to
existing business processes. To be successful with BPM, a
company must fully understand it’s own business processes
and activities that support each area of business.
Advancements in technology continue to change all
businesses. Regardless of activity, it has become imperative
for companies to clearly identify their cyber and network-
related opportunities and avail the right form of insurance
mechanism.
6. CONCLUSION
We have presented a framework that has incorporated the
Data Warehouse building initiative for its effective
operational performance. Insurance data warehouses store
data that is old. The reason why the insurance companies need
this deep history of old data is for several historical
transactions processing. In almost every business the
argument is made that the business in which the organization
was engaging 50 years ago has very little to do with the
business of today. But this is not true in the case of insurance.
There are many labour-intensive processes that impact bottom
line as operational expenses. Data warehousing not only helps
lower those cost, but variabalize them through transaction
pricing. Data Warehousing provides technology-based
solutions to integrate operations and lower application
building and maintenance costs.
Most organizations have a finite and short business cycle. In
an insurance environment, a claim is made and it may be five
years later before the claim is settled. Alternatively, a policy is
purchased and is in force and the final rates are determined six
months later. Alternatively, a renewal has a two months grace
period before the policy is closed. In a word, the speed at
which the insurance environment works is quite different from
the speed at which other organizations operate. Sensing this
need insurance company embraced Data Warehousing
technology for real time quick operations.
This difference in operations-speed will be reflected in the
insurance data warehouse in near future. The resultant need
for new products and services and sustaining competitive
advantage still is a serious challenge for insurance market.
This requires all stakeholders like the insuring customer, the
regulator and the carriers etc all of whom need to work
overtime to cope, in the face of a decontrolled but tightly
regulated market place.
Managing and optimizing business performance is a critical
requirement not only for maximizing business profitability but
even for remaining in viable in today’s fast moving and
competitive business environment. Effective business
performance management will blend business intelligence
with elements of planning, budgeting and real time
monitoring as well as providing a window on performance.
The integration of business and IT process management and
Business Intelligence is the first step in managing business
performance. Finally, BPM is all about taking a holistic
approach for managing business performance. The holistic
approach enables the integration and use of business
intelligence, process management, business service
management, activity monitoring and corporate performance
management to achieve a single and complete view of the
enterprise.
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doc_305221881.pdf
Design of Integrated Business Intelligence System Framework for Insurance Business Processes
International Journal of Applied Information Systems (IJAIS) – ISSN : 2249-0868
Foundation of Computer Science FCS, New York, USA
Volume3, No3., July 2012 – www.ijais.org
42
Design of Integrated Business Intelligence System
Framework for Insurance Business Processes
Dilbag Singh
Deptt. of Comp. Sc. & Applications
Ch. Devi Lal University, Sirsa (HR), India
Pradeep Kumar
Deptt. of Comp. Sc. & Applications
Ch. Devi Lal University, Sirsa (HR), India
ABSTRACT
Business intelligence is a key means to promote core
competence of enterprise. The high construction cost of
business intelligence severely limits the popularization
and development of business intelligence system.
Business process management (BPM) is a key business
initiative that enables companies to align strategic and
operational objectives with business activities in order to
fully manage performance through better informed
decision making and action. Effective business
performance requires an organization to model and
monitor not only its tactics but also its strategies and the
assumption on which these strategies are built. Decision
making is an important task for enterprise managers, and
is typically based on various data sources derived from
information systems, such as enterprise resource planning,
supply chain management and customer relationship
management. Numerous business intelligence tools (BI)
thus have been developed to support decision making.
Some existing BI tools have several limitations, for
example lacking data analysis and visualization
capabilities. The aim of this paper is to examine the
processes, methodologies and technologies underlying
BPM in insurance, the relation between BPM and
business intelligence, and to propose a framework for
integrating corporate performance management and
business intelligence.
Keywords
Insurance, business intelligence, business process,
framework
1 INTRODUCTION
In the past years, companies have understood the
importance of enforcing achievement of the goals defined
by their strategy through metrics-driven management.
Insurance organizations have vast technology assets to
assist them with day-to-day operations, regulatory
compliance, and financial reporting. Such systems record
transactions and manage operational processes, automate
compliance and controls, and roll up financial
performance data. To varying degrees, these systems
populate data warehouses (DW) that are exploited by
business intelligence (BI) systems. [1] The DW process,
though supporting bottom-up extraction of information
from data, fails in top-down enforcing the company
strategy.[2] The missing element, one that finance and IT
teams are now pursuing, is the integration of these
systems into a unified source of performance information
and analysis capability.
Early adopters of business process management have
focused on making the finance function more strategic –
mainly because people have tended to trust data coming
out of a financial system more than other corporate
systems, such as ERP or CRM. Almost every major
business function has a performance management element
that can be realized.[22] To enable this requires
organizations to put in place the right data platform and
source data and ensure that strategic thinking is driven by
the wider needs of the business. Organizations of all
shapes, sizes and markets are under pressure to conform to
increased regulatory compliance pressures and have a
need to link corporate performance to the decision-making
process. BPM can be the right answer in the same
direction.[23]
Now a days knowledge has become a key economic
resource [4] and been an important means to form the core
competence and obtain competitive advantage for all
kinds of enterprises. Knowledge is embedded in the
routine business data, such as consumption records of
customers, sales orders for dealers and supply voucher of
provider. To discovery the knowledge from those data
could effectively aid enterprises in scientific decision-
making and analysis.[5] Transforming the customer and
operational information into knowledge, Business
Intelligence (BI) provides the consolidation and analysis
of raw data, and the capacity of processing raw data into
the executable decision-making information. It could
enhance the competitiveness of enterprises by using
different sources from customers, operations and market
information [6].
The aim of this paper is to examine the processes,
methodologies and technologies underlying BPM in
insurance, the relation between BPM and business
intelligence, and to propose a framework for integrating
corporate performance management and business
intelligence. The proposed BI system can potentially be
considered as an efficient data analysis tool for supporting
business decisions.
International Journal of Applied Information Systems (IJAIS) – ISSN : 2249-0868
Foundation of Computer Science FCS, New York, USA
Volume3, No3., July 2012 – www.ijais.org
43
2. BUSINESS INTELLIGENCE
The various operational and transaction data can be
transformed into information and then knowledge by
using business intelligence (BI) tools. Enterprises decision
makers make better business decisions based on
systematic acquisition, collation, analysis, interpretation
and exploitation of information. BI components comprise
online analytical process (OLAP), knowledge
management, customer relationship management (CRM),
visualization, decision support system/executive
information system, data mining (DM) and geographic
information system (GIS) [11,15]. Wingyan et al. [6]
indicates that existing BI tools suffer several limitations,
such as poor data analysis and visualization capabilities.
Many advanced BI tools have been developed to
overcome weaknesses, including HP Openview
DecisionCenter [10] and Microsoft SQL Server 2008 [8].
Moreover, Michalewicz et al. [9] introduced a scheme of
an adaptive BI system, which combines optimization,
prediction and adaptability. The adaptive BI system is
capable of answering two questions:[16]
(1) ?What is likely to happen in the future??
(2) ?What is the best decision right now??
Li et al. [12] indicate that BI comprises concepts, methods
and process to improve business decisions, which employ
information from multiple sources, and use experience
and assumptions to develop an accurate understanding of
business dynamics. BI has several objectives [7]:
? to gather data from various sources;
? to transform this data into information and then
knowledge;
? to provide a friendly graphic interface to display
this knowledge.
Figure 1 illustrates the BI process, which works to
transform data into information, and then knowledge
using analytical tools, such as DM, OLAP, visualization
etc. Finally, the generated knowledge can be used to
support business decisions. BI systems have been used to
many application fields, such as ERP, SCM, CRM and
human resource management. [13]
Figure-1: BI Process
3. BI TECHNOLOGIES AND
BUSINESS PROCESSES
BI is composed of three core components, namely data
warehouse(DW), online analytical processing(OLAP)
and data miming(DM), where DW is the basis of BI
which provides comprehensible and accurate data
support for the other two components [14]. With the
development of global economic integration process,
enterprises in the world have broken through the national
border to carry out the manufacture, operation, and
service. Therefore, in construction of BI systems
enterprises need to consider the following [18]:
Distributed user circumstance: Global economic
integration makes various types of users in enterprise to
distribute in different area of the world. It needs BI
system to adapt to a distributed user circumstance.
Distributed data circumstance: Enterprises carry out
activities on a global scope which result in the global
distribution of business data. These data is the basis of
the formation of BI. Therefore it needs BI system to
adapt to a distributed data circumstance.
Heterogeneous data resources: The various business
processing systems of enterprise, such as ERP, CRM,
and SCM and so on, produce large amounts of business
data every day. These data is heterogeneous, redundant
and isolated each other. It needs BI system to integrate
heterogeneous data resources.
Organizations make choices and decisions based on the
quality of the information at their disposal. Data
warehousing can be the key factor for providing
management with the right information at the right time
to make solid choices, allowing key decision makers to
examine business trends and establish solid strategy for
the future.[17] Data Warehousing is believed to be a
competitive necessity. The management of knowledge
supports the competitive advantage of organizations.
Therefore, the effective use of data warehousing
(McManus and Snyder, 2003) to store knowledge can be
instrumental in supporting the competitive advantage of
companies. Considering the extensive size of the
database itself, the data warehouse is in a permanent state
of redesign in its model and structure. Having a massive
database is useless unless the relevant information is
retrieved quickly on request by the end user in real time
basis [20].
Productio
n Data
Internal
Data
External
Data
Archived
Data
Data
Staging
(ETL)
MDDB
Informatio
n
.
.
Data
Mining
OLAP
Report/
Query
Visualizat
ion
Knowledg
e
Decision
Data
Mart
Data
Warehous
e
International Journal of Applied Information Systems (IJAIS) – ISSN : 2249-0868
Foundation of Computer Science FCS, New York, USA
Volume3, No3., July 2012 – www.ijais.org
44
? Organizations need to have better and
enhanced business intelligence in reduced time
for the end users for efficient and effective
decision making.
? Consolidation of heterogeneous information
sources is a must for any firm to achieve
strategic advantage over competitors in the
market and market products and services at a
faster level.
? Replacement of older, less responsive decision
support systems is an important requirement to
reduce dependence on Information Systems
(IS) to generate reports.
The traditional implementation of BI is to extract data
from various business processing systems or local data
sources, transform and load data to DW at central site via
computer network. [19] Then DW-oriented analysis and
mining are carried out. It benefits scientific and effective
decision making of enterprise [21]. Oriented to the
current applied status, the traditional implementation
method requires enterprises to provide high-speed data
transmission networks, high-capacity data storage at
central site. It brings a heavy financial burden to
enterprises, especially to small and medium enterprises
which possess poor resource. To enhance scientific
decision-making and analytical capacity of the vast
number of domestic traditional enterprises and small and
medium enterprises in international competitiveness, this
paper takes the advantages of multi-agent technology to
give a low-cost BI systems design which can reduce the
construction cost of BI system and extend the applied
scope of BI by minimizing the amount of data transfer
and data storage. [24, 25]
Any BI implementation is aimed at turning available data
into information and delivering it to the decision makers.
BPM is focused on a subset of the information delivered
by a BI system – the information that shows business
performance and indicates business success or failure
and enables organizations to focus on optimizing
business performance. [22]
BPM involves a closed-loop set of processes that link
strategy to execution in order to respond to that task.
Optimum performance is achieved by:
? Setting goals and objectives – strategize
? Establishing initiatives and plans to achieve
these goals –plan
? Monitoring actual performance against the
goals and objectives – monitor
? Taking corrective action – act and adjust
The key to effective BPM is tying performance metrics
to business strategy, and that means a melding of two
areas of technological functionality: strategic
management systems and performance metrics.
The first are systems that manage the key business
processes that affect strategy execution, including
objective management, initiative management, resource
management, risk management and incentive
management.
The second is essentially a business intelligence platform
for automated data exchange, reporting and analysis.
BPM should produce three core deliverables: [23]
? Information delivery to enable managers to
understand the business.
? Performance oversight to enable them to
manage the business.
? Performance effectiveness to enable them to
improve the business.
Business performance management must be an
enterprise-wide strategy that seeks to prevent
organizations from optimizing local business at the
expense of overall corporate performance.
Business Information Technologies are seen as cutting
edge Information Technologies made on purpose to
support business information engineering. Management
methods, techniques and support tools could be seamless
integrated with Business Intelligence components in
special tailored or customized Performances
management systems. The main functions of these
systems are:
? To gather and store different measures of the
business on a regular basis (current state
indicators of the business performances).
? To gather and store benchmarks and targets
(threshold values) and business rules
(interpretations of comparison results between
current performance’s indicators and etalon
values).
? To facilitate roll-ups and drill-downs of
analyzed indicators along hierarchical
aggregation criteria (structured Performance
Measurements).
? To keep the ongoing analysis alert - allowing
decision makers to quickly evaluate which
business processes are successful, and which
need their attention.
To summarize, an effective Business Performance
Information System is built and maintained by business
users to support the decision-making process especially
at strategic level, making use of various indicators –
quantitative and qualitative, lagging and leading –
balanced against targeted objectives and/or industry
benchmarks. Lastly, with performance measurement
periods becoming shorter, management must have the
capability to more proactively influence the outcome.
That requires monitoring and tracking capabilities that
can generate current, complete and accurate information
upon which they can act in real time. Business
information technologies must respond to that need of
proactively managing business performance.
4. BI AND INSURANCE BUSINESS
PROCESS MANAGEMENT
Business intelligence can be considered as being the final
component of business process management (BPM) after
the decision support systems, enterprise information
International Journal of Applied Information Systems (IJAIS) – ISSN : 2249-0868
Foundation of Computer Science FCS, New York, USA
Volume3, No3., July 2012 – www.ijais.org
45
systems. If BPM is an outgrowth of BI and incorporates
many of its technologies, applications and techniques,
than why BI itself can’t deliver the insight needed to
improve overall business performance? From a
theoretical viewpoint, it can. From a practical standpoint,
it hasn’t. Like decision support; BPM is more than a
technology. It involves the processes, methodologies,
metrics and technology used to monitor, measure sand
manage a business. Once selected the business process
that has to be improved, and the business methodology to
be implemented, there are the metrics (to monitor,
measure and change) to be established. These metrics
(key performance indicators) are defined and selected by
the business and not by the IT. The final step is to choose
the business performance measurement technology. We
can say that business intelligence it is just business
measurement and not business performance
management. BPM is not a single technology, but rather
a combination of elements – BI, score carding, profiling.
BI looks at and analyses the past and what has happened
up until today – this is useful, as planning requires
knowledge and you can set planning goals based on the
past. Score carding enables you measure how you are
performing against those planned goals. Every
organization has processes in place that feed back to the
overall plan. [26]
What’s new with BPM is the integration of these
processes, methodologies, metrics and systems – an
enterprise wide strategy that seeks to prevent
organizations from optimizing local business at the
expense of overall corporate performance.
The industry is looking to improve its performance in
various areas: improved quality of underwriting, multiple
options of premium payment, enhanced claims
management processes, easy way of renewal,
discontinuation of policy , better management of the
exposure/risks created from declining investment returns
and the development of better business controls and
reporting, both operationally and financially[26]. Apart
from these core areas, insurers are looking at increasing
channels of distribution, which affects the profitability of
their business, through alliances. The various areas of
this sector in which business intelligence is required are
[27]:
Sales and Marketing: Analyse customer behaviour and
buying patterns to create new products and services that
help sales teams to meet revenue goals. Identification of
cross selling/ upselling opportunities involves
identification of those customers in the existing database
whose likelihood of responding to a product which they
do not hold presently is the highest.
Claim Fraud Detection & Prediction: Identify
fraudulent patterns and use historical data to uncover past
fraud cases. Improve cost saving with more efficient and
effective fraud detection. The analytic solutions which
help manage the complex claims process effectively and
help detect fraud by accurately forecasting likely
outcomes in order to mitigate the severity of the claim.
Customer Segmentation/Classification: It is extremely
important for insurer to segment customer based on their
behavior and potential profitability. Analytics can help
them more accurately, which policies and services to
offer to which customers. Apart from customer
segmentation, data mining can also be used to predict the
likelihood of policy cancellation in advance.
Market/Product Analysis: As there are several products
to cater the need of various customers. Which product is
suitable for the customer demographics? Planning and
launching of new product for the targeted customers.
Risk Management: To adapt a risk based approach,
insurers will have to implement an economic capital
regime, where they predict and evaluate the risk profile
of the underwritten business under both best case and
worst case scenarios. Simulation techniques and
stochastic model for various risk such as credit market
liability; underwriting and operational risk can be used
for scenario and stress testing to determine the optimum
economic capital level.
5. DESIGN OF INTEGRATED BI
FRAMEWORK FOR INSURANCE
The integration of business and IT process management
and BI is a key enabler for BPM. It provides the ability
to effectively manage the business and achieving
business goals.
The BPM framework presented below is based on the
integration of business and IT processes at all decision
levels (strategic, tactical and operational).
In the figure-2, the various BI users are Market Product
Research, Business development, Insurance consultant,
Customer service, Management /DSS. Outside Databases
includes data that are acquired from external
market/industry research and multiple insurers in
different formats. Company/product Databases includes
insurance company/product analysis information,
Product terms, fee rate, company analysis/rating
information, etc. Operation Databases includes various
kinds of operation information such as customer
information (customer purchased product, buying
behaviour, customer service), sales information (sales
performance, productivity, activity management), etc.
A set of powerful Data Warehouse applications are built
based on this infrastructure. Multiple well-established
databases provide the following services to Data
Warehouse users:
? CRM services (for Business Development
and Customer Service Dept.) - in-depth
analysis of customer value, needs, buying
behavior, service requirements, etc. are
provided to support more effective and targeted
customer development and customer services.
? Sales management services (for Sales Mgmt
Dept.) - in-depth analysis of sales team
productivity and performance are provided to
support tailored management, training and
coaching efforts.
? Market/product analysis services (for
Research Dept.) - accumulated product sales
data and market research data are used as input
to adjust product-selecting approach and guide
strategic direction of future development.
International Journal of Applied Information Systems (IJAIS) – ISSN : 2249-0868
Foundation of Computer Science FCS, New York, USA
Volume3, No3., July 2012 – www.ijais.org
46
Figure-2: Integrated BI framework for insurance
? Management and decision supporting services
(for Management) - management/ operation
performance tracking analysis are provided based
on integrated OLAP (Online Analytical Processing),
data mining technologies to support key
management decisions to ensure market
competitiveness.
Business intelligence is a business management term, which
refers to applications and technologies that are used to gather,
provide access to, and analyze data and information about
company operations. Business intelligence systems can help
companies have a more comprehensive knowledge of the
factors affecting their business, such as metrics on sales,
production, internal operations, and they can help companies
to make better business decisions.
Business flexibility and agility require continuous monitoring
of the business processes and support of an appropriate BI
environment. An environment that provides information
sufficiently current (near real time) to support the
requirements for both operational and strategic decision
making. BI technologies and products are evolving in order to
provide such an environment, and we can list only some of the
new trends:
? linking business process data to operational activity
data for a complete for a complete view of the
enterprise;
? implementation of business rules and Key
Performance Indicators to enable consistent
management of the business activities;
Data Warehouse
MDDB
Data Mart
Meta Data
Outside data source
Company Database Other data source
Underwriting/Pre
mium Payment
Claim
Surrender
Partial Return /
Maturity Return
BI User 1
BI User 2
BI User 3
BI User n
OLAP / Data
Mining
Information
Subject 1
(Sales &
Marketing)
((
Information
Subject 2
(Fraud
Detection)
Information Subject
3
(Cust Classification
& Prediction)
Information
Subject n
(Risk
Management)
Information
Subject 4
(Mkt/Product
Analysis)
International Journal of Applied Information Systems (IJAIS) – ISSN : 2249-0868
Foundation of Computer Science FCS, New York, USA
Volume3, No3., July 2012 – www.ijais.org
47
? automatic alert generation for proactive problem
avoidance rather than reactive problem impact
minimization;
? real time data flow to enable monitoring and
proactive management of business processes.
A BI environment that include these capabilities enables
companies to proactively manage their businesses, rather than
just react and adjust to business situations as they arise. The
main objective of BPM is to help companies improve and
optimize their operations across all aspects of their business.
But implementing BPM is much more than just about
choosing new technology – it suppose a constant analyze of
business environment to determine if changes are required to
existing business processes. To be successful with BPM, a
company must fully understand it’s own business processes
and activities that support each area of business.
Advancements in technology continue to change all
businesses. Regardless of activity, it has become imperative
for companies to clearly identify their cyber and network-
related opportunities and avail the right form of insurance
mechanism.
6. CONCLUSION
We have presented a framework that has incorporated the
Data Warehouse building initiative for its effective
operational performance. Insurance data warehouses store
data that is old. The reason why the insurance companies need
this deep history of old data is for several historical
transactions processing. In almost every business the
argument is made that the business in which the organization
was engaging 50 years ago has very little to do with the
business of today. But this is not true in the case of insurance.
There are many labour-intensive processes that impact bottom
line as operational expenses. Data warehousing not only helps
lower those cost, but variabalize them through transaction
pricing. Data Warehousing provides technology-based
solutions to integrate operations and lower application
building and maintenance costs.
Most organizations have a finite and short business cycle. In
an insurance environment, a claim is made and it may be five
years later before the claim is settled. Alternatively, a policy is
purchased and is in force and the final rates are determined six
months later. Alternatively, a renewal has a two months grace
period before the policy is closed. In a word, the speed at
which the insurance environment works is quite different from
the speed at which other organizations operate. Sensing this
need insurance company embraced Data Warehousing
technology for real time quick operations.
This difference in operations-speed will be reflected in the
insurance data warehouse in near future. The resultant need
for new products and services and sustaining competitive
advantage still is a serious challenge for insurance market.
This requires all stakeholders like the insuring customer, the
regulator and the carriers etc all of whom need to work
overtime to cope, in the face of a decontrolled but tightly
regulated market place.
Managing and optimizing business performance is a critical
requirement not only for maximizing business profitability but
even for remaining in viable in today’s fast moving and
competitive business environment. Effective business
performance management will blend business intelligence
with elements of planning, budgeting and real time
monitoring as well as providing a window on performance.
The integration of business and IT process management and
Business Intelligence is the first step in managing business
performance. Finally, BPM is all about taking a holistic
approach for managing business performance. The holistic
approach enables the integration and use of business
intelligence, process management, business service
management, activity monitoring and corporate performance
management to achieve a single and complete view of the
enterprise.
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