Description
The purpose of this paper is to analyze the income structure of Islamic banks in the Gulf
Cooperation Council (GCC) countries and to explore the effect of the diversification of banks’ earning
on risks that may harm these latter.
Accounting Research Journal
Islamic banks' income structure and risk: evidence from GCC countries
Rihab Grassa
Article information:
To cite this document:
Rihab Grassa, (2012),"Islamic banks' income structure and risk: evidence from GCC countries", Accounting
Research J ournal, Vol. 25 Iss 3 pp. 227 - 241
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http://dx.doi.org/10.1108/10309611211290185
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Lucia Dalla Pellegrina, (2012),"Does capitalization enhance efficient risk undertaking?: A comparison
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dx.doi.org/10.1108/10309611211290167
Ismail Cebeci, (2012),"Integrating the social maslaha into Islamic finance", Accounting Research J ournal,
Vol. 25 Iss 3 pp. 166-184 http://dx.doi.org/10.1108/10309611211290158
J ose Francisco Rubio, M. Kabir Hassan, Hesham J amil Merdad, (2012),"Non-parametric performance
measurement of international and Islamic mutual funds", Accounting Research J ournal, Vol. 25 Iss 3 pp.
208-226 http://dx.doi.org/10.1108/10309611211290176
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Islamic banks’ income structure
and risk: evidence from GCC
countries
Rihab Grassa
University of Manouba, Tunis, Tunisia
Abstract
Purpose – The purpose of this paper is to analyze the income structure of Islamic banks in the Gulf
Cooperation Council (GCC) countries and to explore the effect of the diversi?cation of banks’ earning
on risks that may harm these latter.
Design/methodology/approach – Using data from 2002-2008 for 42 Islamic banks, this article
provides descriptive and analytical analysis and multiple regression equations.
Findings – This article reveals that greater reliance on the income share of the pro?t-loss-sharing
products is associated with higher risk and higher insolvency risk for both listed Islamic banks and
non-listed Islamic banks. However, no effect has been observed between the operation income of
non-pro?t-losses-sharing products and risk levels. That is why listed banks prefer to invest less in
non-pro?t-loss-sharing products than in pro?t-loss-sharing products.
Research limitations/implications – Financial regulators in emerging Islamic ?nancial market
should help Islamic banks to ?nd equilibrium between the expansion of the Islamic ?nancial market
and respect for the raison d’e ˆtre of Islamic ?nance: the pro?t and loss sharing mechanisms.
Originality/value – To the best of the author’s knowledge, this is the ?rst article that empirically
tests why Islamic banks prefer to invest less in pro?t-loss-sharing products. Also, this article
contributes to studying the relationship between Islamic ?nance and risk.
Keywords Saudi Arabia, Kuwait, United Arab Emirates, Qatar, Bahrain, Islam, Banks, Islamic banks,
Risk management, Performance, Pro?t-loss-sharing products
Paper type Research paper
1. Introduction
Today Islamic banking system in Gulf Cooperation Council (GCC) countries is facing
many changes in the form of increased competitions in the ?nancial market,
concentration and restructuring. Islamic banks have reacted to the new environment of
the ?nancial market by adopting a proactive strategy by diversifying the range of
Islamic ?nancing products offered to their customers. These changes have mainly lead
Islamic banks to diverge from their classical pro?t losses sharing ?nancing scheme to
another ?nancing system that presents more advantages for them. Hence, an important
share of pro?t and losses sharing ?nancing products has been given to non-pro?t and
losses sharing products. As a result, the structure of the bank income experienced
a dramatic change.
Most of the existing studies focusing on the portfolio diversi?cation effect explored
the Western context and more especially the conventional-banking system. However,
no articles have studied empirically the portfolio diversi?cation effect of the Islamic
?nancial system.
The purpose of this paper is to evaluate the risk implications of the diversi?cation
structure of Islamic banks in GCC countries which has shifted away from
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1030-9616.htm
Islamic banks’
income structure
227
Accounting Research Journal
Vol. 25 No. 3, 2012
pp. 227-241
qEmerald Group Publishing Limited
1030-9616
DOI 10.1108/10309611211290185
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pro?t-losses-sharing activities to others nonpro?t-loss-sharing activities but
also permitted by Shari’a scholars to discuss the way of such behavior. Through
using a sample of Islamic bank data from 2002 to 2008 for 42 Islamic banks, we start
by the output diversi?cation that is measured by two indicators, the income share of
(i) pro?t-loss-sharing income and the nonpro?t-loss-sharing income of (ii). In the
beginning, we start by comparing the risk level of Islamic banks which use more
pro?t-loss-sharing ?nancing method with the risk level of Islamic banks which have
preferred to invest more in nonpro?t-loss-sharing ?nance. Our ?ndings show that
higher reliance on pro?t-loss-sharing ?nancing activity is strongly associated with
higher risk, and our study shows that Islamic banks expanding into pro?t-loss-sharing
products present higher risk and higher insolvency risk than banks which invest less
in this kind of arrangement. Additionally, listed bank prefer to invest less in
nonpro?t-loss-sharing products than pro?t-loss-sharing products. This behavior can be
explained by the fact that Islamic banks focus more on the ?nancial stability of their
investments. Islamic banks as an equity-based capital structure dominated by
shareholders equity and investment deposit holders have to offer a competitive
remuneration to them especially to the deposit holders. Indeed, in a competitiveness
?nancial market like the GCC market, customer will be more sensitive to the volatility of
returns offered on investment deposit and may withdraw their funds in case of low
remuneration.
The article proceeds as follows: in Section 2, we review the following studies about
pro?t-loss-sharing paradigm and Islamic banks attitudes, studies about bank risk and
product diversi?cation and we show how our study extends the existing work about
Islamic ?nance. In Section 3, we present a description of the context of our study.
In Section 4, we reveal the methodology adopted in this paper. In Section 5 we present
and discuss the results of our regression analysis. Finally, in Section 6 we summarize
the ?nding of the paper.
2. Literature review: pro?t-loss-sharing paradigm and Islamic banks
attitude
Islamic ?nance is based on Quran law that forbids all form of interest and especially
interest charging on loan (Roy, 1991). The hostility towards the interest is based on the
belief that the Islamic religious book forbids all forms (Kuran, 1995). In fact, one of the
most important instructions of Islam to establish justice and eliminate immoral
exploitation in commercial transactions is the prohibition of all sources of “unfair
enrichment” (Chapra, 1997). As a matter of fact, the Islamic holy book considers “Riba”
(usury) as one of the sources of unjust enrichment. According to Shari’a, the riba
banned by Islam refers to the “premium” to be paid by the borrower or to the lender
in addition to the principal amount as a condition to the credit or the extension of its
maturity. In other word, it is the addition in the amount of the principal of a loan
according to the time and the amount of the loan (Suleiman, 2000). In this sense, riba
has the same meaning and is considered as an interest form (Chapra, 1997).
However, Islam distinguishes between money and capital. To transform money to
capital there is a need for an enterprise application. Consequently, there is the risk
taking and the required knowledge to bring factors of production jointly in order to
generate return (Presley, 1988). If the lender provides project in any form, he has to
justify a pro?t (or loss) share, but not a ?xed or a certain return; the prize. That is to say,
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the pro?t share is determined by contribution in terms of enterprise. So, the relationship
between creditor/debtor that we can see in conventional economy is rede?ned in Islam.
The creditor becomes a partner in the project, not distanced from the use in which
his money is employed. Indeed, Islamic economic perspective distinguishes the “rate of
interest” fromthe “rate of return”. On the one hand, Islamundoubtedly forbids receiving,
payment and trading with charging interest and on the other hand, it encourages trade.
Indeed, inthe interest-free system(the Islamic system), people are able to earna returnon
their money just by subjecting themselves to the risk involved in pro?t sharing. Since
the use of interest rates in ?nancial transactions is banned and the partnership is
encouraged, Islamic scholars think that banks should undertake operations only on the
basis of “pro?ts and loss sharing” arrangements or other acceptable modes of ?nancing.
That is why; the idea of Islamic bank came into surface. Islamic banks are ?nancial
institutions that are expected to undertake operations only on the basis of pro?t and loss
sharing arrangements or other “acceptable” means of ?nancing by Shari’a. In this
context, the relationship between creditor/debtor that we can observe in conventional
economy is rede?ned and the creditor becomes a partner in the project by sharing the
pro?t, supporting the losses and sharing the risks (Siddiqui, 2004; Dar and Presley, 2000;
Sudin, 1996; Lewis, 2007). So, Islamic bank is a ?nancial institution that receives
deposits and carries all banking activities except operations of lending and interest
based activities. The banks’ liabilities are constituted by all mobilized founds through
Mudaraba operation. Bank assets are formed by all advanced funds used in
pro?t-loss-sharing’ based techniques or all other operations permitted by the Islamic
law. An Islamic bank is a ?nancial intermediary mobilizing savings from the public on
Mudaraba basis and advancing capital to entrepreneurs on the same basis
(Suleiman, 2000).
Most theoretical models of Islamic banking are based on the Mudaraba
(pro?t-sharing) and/or Musharaka ( joint venture) concepts of pro?t-loss-sharing
(Dar and Presley, 2000). However, most of Islamic banks use other ?nancing contracts
that are permissible in Islam but not strictly pro?t-loss-sharing in nature. Such
?nancing contracts may be based on Murabaha (cost plus), Ijarah (leasing), Bai’ muajjal
(deferred payment sale), Bai’Salam (forward sale), and Istisna (contract manufacturing)
concepts.
During the last decade, many researches ?nd that Islamic banking, as it is practiced
today, tends to deviate substantially from the pro?t-loss-sharing paradigm. Ibrahim
(2006) ?nds that 34 percent of the investments of the Sudanese’s’ Islamic banks are a
pro?t-loss-sharing investments. However, nonpro?t-loss-sharing investments are
nearly 50 percent. Sudan’s bank explains this attitude in its Annual Report of 2001,
that the substantial use of other mode of ?nancing than pro?t-loss-sharing mode,
especially Murabaha, in Sudanese banking system is due to “the simplicity of this
mode and the people’s preference” (Bank of Sudan, 2001). While, Yusuf (1996) ?nds
that during the period 1980-1990, the share of the pro?t-loss-sharing investments were
in the range of 33 and 38 percent for Iranian banks and in the range, the
nonpro?t-loss-sharing techniques shared around 51-60 percent for Iranian banks.
Chang and Liu (2009) ?nds that, in Malaysian context pro?t-loss-sharing products
represented only 0.5 percent of the total ?nancing offered by Islamic banks in Malaysia
however Murabaha represented 49.9 percent Islamic bank ?nancing in Malaysia, in
practice, is still based largely on nonpro?t-loss-sharing modes of ?nancing that
Islamic banks’
income structure
229
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are permissible under the Shari’ah whereas, Matoussi and Grassa (2010) ?nd that
during the period 2002-2008, on average, the share of the nonpro?t-loss-sharing
?nancing on the total ?nancing made by Islamic banks in GCC countries is
85.27 percent and generates 70 percent of the income of Islamic banks income.
However, only 14.73 percent Islamic banks ?nancing in GCC countries was
pro?t-loss-sharing ?nancing and generate 30 percent of the total Islamic banks income
in GCC countries.
The small share allocated by Islamic banks to the pro?t-loss-sharing ?nancing even
the high return of these products, can be explained by the fact that pro?t-loss-sharing
?nancing products are more risky, require more costly monitoring and encounter
several inconveniences due to the lack of management and control right. In fact,
Musharaka ?nancing encounters moral hazard problems associated with ex post
information asymmetry, the entrepreneur (borrower); for example has an incentive to
under-declare or arti?cially reduce reported pro?t (Mills and Presley, 1999). Besides, in
the case of Mudaraba contract, the entrepreneur has an incentive to undertake
high-risk projects because the entrepreneur is actually given a call option whereby he
or she gains on the upside but bears no losses at all on the downside. Also, in
Mudaraba ?nancing, the bank provides all the risk associated with the capital, but the
management and control of the project are mostly in the hands of the entrepreneur.
This think accentuates the principal-agent problems associated with
pro?t-loss-sharing ?nancing (Dar and Presley, 2000). Nevertheless, Ibrahim (2006)
explains the lower percentage of pro?t-loss-sharing investment by the fact that non
pro?t-loss-sharing ?nancing contract satis?es the need of the majority customer of the
bank more than pro?t-loss-sharing ?nancing mode.
Most of the studies explained theoretically the relationship between Islamic
?nancial products and the risk taking by Islamic banks. However, to our knowledge,
there are no researches that tried to explore this subject empirically. As well, little
studies have focused on the effect of the bank income structure on risk taking. Most of
them focus on the conventional ?nancial context. DeYoung and Roland (2001)
concludes that fee-based activities increase the volatility of banks revenue in the USA.
Stiroh and Rumble (2006) ?nd similar results for US ?nancial holding companies
observed during the period 1997-2002. Lepetit et al. (2007) ?nd that European banks
expanding into non-interest income activities present higher risk and higher
insolvency risk than banks mainly supply loans. However, no article has studied the
effect of the diversi?cation of the Islamic banks’ earning on risks.
This paper tries to explore the effect of the earning diversi?cation on the Islamic
banks’ risk. Hence, to our knowledge, this is the ?rst study that explores the impact of
the diversi?cation of Islamic banks’ earning on risk in the case of GCC countries.
In the next section, we will present the methodology adopted in this research and the
context of our study.
3. Context of study: Islamic banking in GCC countries
The GCC consists of six countries located in the Middle East: Saudi Arabia, Kuwait,
United Arab Emirates, Qatar, Oman and Bahrain. The GCC was founded in 1981 with
the objective of coordinating policies of various political, economic, and social matters,
and have similar regulations. The GCC countries are independent governments with
independent currencies. Oil, which is the main commodity of these countries, was
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discovered in the 1940s in GCC countries and constitutes today the world’s largest
reserve. Banking industry development in GCC countries is linked to oil export.
Since the oil boom of the 1970s, foreign banks are installed in GCC countries. Early
banking in the GCC region experienced a lot of foreign ownership mostly by a bank
named British Bank in the Middle East. This bank had branches across all six GCC
countries. Other foreign banks were also popular as there were large revenues from oil
trade. Local banks were not common because of lack of suf?cient experience. Since
1975, the Islamic bank industry was developed in GCC. The ?rst Islamic banks
implanted in GCC countries were the Kuwait Finance House, Dubai Islamic Bank and
Al-Rajhi bank in Saudi Arabia. The GCC region currently remains the primary
?nancier of Islamic ?nance world-wide. By the end of 2008, there were more than
45 Islamic banks in GCC, which used to offer a full range of Islamic banking products
and services. Today, the GCC countries are widely believed to have the most developed
Islamic ?nancial system in the world that operates side-by-side with a
conventional-banking system. A part from the interest-free banking scheme, the
GCC countries have a well-developed Islamic interbank money market, Islamic
securities market, and Islamic insurance market.
Seeing the signi?cant growth of the Islamic ?nance, several GCC countries have
installed a comprehensive prudential and reporting framework, tailor-made for the
speci?c concepts and needs of Islamic banking and insurance. In addition to the
numerous Islamic ?nancial institutions active in its ?nancial sector, GCC countries also
presented as a host to a number of organizations based on the development of Islamic
?nance, including:
.
The Accounting and Auditing Organization for Islamic Financial Institutions
(AAOIFI).
.
The Liquidity Management Centre (LMC).
.
The International Islamic Financial Market (IIFM).
.
The Islamic International Rating Agency (IIRA).
Today, Gulf Islamic banks control a market share with about 15 percent of the regional
banking system’s assets, and have become part of mainstream ?nancial intermediation
in this part of the world. At the same time, Islamic banks in the GCC have also become
more diverse: large pioneers established in the 1970s co-exist with new entrants, former
conventional ?nancial institutions recently converted into fully ?edged
Shari’ah-compliant banking entities and the Islamic windows of still-conventional
banking providers. The total assets of Islamic banks in GCC exceed 125 billion $ (more
than 25 percent Shari’ah-compliant banking assets globally)[1].
According to the International Monetary Fund (October 2009), during the period
2002-2008, in the average, Gulf Islamic banks’ assets represent 23.8 percent of the total
banking assets, and the growth rate of Islamic banks’ assets is over 44 percent (the
growth rate of assets of the global banking system in GCC is over 22.6 percent). Table I
summarizes some data for each GCC country.
4. Methodologies
In this research, we will adopt the methodology used by Stiroh and Rumble (2006) and
Lepetit et al. (2007). We will provide, as well, some modi?cations to adapt the empirical
Islamic banks’
income structure
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model to the particularities of Islamic banks. That is why; we will have three kinds of
variables: Islamic products variables, accounting data based risk measures variables
and control variables.
4.1 De?nitions of variables, data and primary statistics
4.1.1 Islamic products variables: Islamic banks’ income structure. In this research, we
are interested only in Islamic products incomes and we will not take into consideration
the other incomes earned by Islamic banks like commission, transaction fee, etc.
To measure Islamic banks products, we distinguish two components of Islamic
?nancial products income: pro?t-loss-sharing products income (PLS income) and
nonpro?t-loss-sharing products income (Non_PLS income). Hence, we de?ne a ratio of
net PLS income to net operating income (PLS) and a ratio of net Non_PLS income to net
operating income (NON_PLS). Net PLS operating income is equal to PLS income minus
PLS operating expense and net Non_PLS income is equal to Non_PLS income minus
Non_PLS operating expense.
4.1.2 Accounting data based risk measures. In this study, we used two standards of
risk measurement, based on annual accounting data and determined for each bank
throughout the period:
.
the standard deviation of the return on average assets (SDROA); and
.
the standard deviation of the return on average equity (SDROE).
We also compute insolvency risk measures:
(1) The “Z-score” (ADZ) which indicate the probability of failure of a given bank;
the “ZP-score” (ADZP) as in Goyeau and Tarazi (1992) and its two additive
components which we identify ADZP1 and ADZP2. ADZP1 is a measure of
bank portfolio risk whereas ADZP2 is a measure of leverage risk:
.
ADZ ¼ (100 þ average ROE)/SDROE; where ROE and SDROE are
expressed in percentage. Higher values of Z-score imply lower probability
of failure (Boyd and Graham, 1986).
.
ADZP ¼ ADZP1 þ ADZP2 ¼ (average ROA/SDROA) þ (average (total
equities/total assets)/SDROA).
Islamic banks’ assets
in total assets in 2008
Growth rate of
assets (Islamic banks)
Growth rate of
assets
a
(banking
system) Period
Saudi Arabia
b
35 33.4 19 2002-2008
Bahrain
c
29.9 37.6 7.9 2000-2008
Kuwait 29 23.2 14.3 2002-2008
UAE 13.5 59.8 38.1 2002-2008
Qatar 11.5 65.8 31.9 2002-2008
GCC average 23.8 44 22.6 2002-2008
Notes:
a
Including Islamic banks;
b
growth rate is calculated for the total of wholesale and retail while
market share is for retail only;
c
including Islamic windows
Source: International Monetary Fund (2009)
Table I.
Market share and
average annual asset
growth of Islamic and
conventional Banks
in selected countries
(percent)
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ADZP1 ¼ average ROA/SDROA.
.
ADZP2 ¼ average (total equities/total assets)/SDROA.
4.1.3 Control variables. Following prior studies, we include several bank characteristics
in the empirical analysis. Log assets is the log of total assets at the end of the year t.
Loan ratio is the loan scaled by total assets for the year t. ROE is the return on equity
ratio for the year t. For the country speci?c characteristics we will use the ratio Cont_C.
Cont_C is the ratio Islamic banks assets to total banks assets in year t in each country.
4.2 Data
We use a sample consisted of an unbalanced panel of annual report data from 2002 to
2008 for a set of Islamic banks in ?ve countries of GCC: Bahrain, Qatar, Kuwait,
Kingdom of Saudi Arabia, United Arab Emirates (Table II). We collect data for our
research from the annual reports of Islamic banks in GCC countries. Since the number
of banks has been increasing every year, we select banks existing for at least three
years (since 2005). Our ?rst sample is consisted of 45 Islamic banks in GCC countries.
We have excluded one bank because it was part of a non-Islamic bank group, hence it
is not possible to distinguish from their annual reports between the Islamic and the
non-Islamic investments or revenue. We also excluded two other banks because
the lack of information. Our ?nal sample is constituted of 42 banks observed during
the period 2002-2008. Many Islamic banks in our sample do not use the AAOIFI
presentation for their ?nancial statements. Hence, the balance sheet and the income
statement cannot help us to distinct between pro?t-loss-sharing and
nonpro?t-loss-sharing amounts. However, Islamic banks disclose such information
in the notes to the ?nancial statement.
5. Results
5.1 Descriptive statistics
Descriptive statistics of our sample are presented in Table III. The share of the income of
the Islamic ?nancing products represented, in average, 61.87 percent of the total Islamic
bank income. Both samples show suf?cient heterogeneity in different types of banking
activities. In the average, 19.07 percent of the incomes of Islamic banks come from
pro?t-loss-sharingproducts (16.45 percent for listedbanks and22.89 percent for non-listed
banks). Whereas on average 42.80 percent of the incomes of the Islamic banks come from
nonpro?t-loss-sharing products (45.10 percent for listed banks and 38.11 percent for
non-listedbanks). Listedbanks make more income fromnonpro?t-loss-sharingandhave a
higher ROE than none listed banks. However, non-listed banks earn more income from
pro?t-loss-sharing and had a higher ROA that listed banks.
5.2 Univariatemeans tests
We split our sample into different panels of banks. We compare the level of risk of
banks which are characterized by high levels of pro?t-loss-sharing activities that is
2002 2003 2004 2005 2006 2007 2008
Islamic banks 10 12 25 32 42 42 42
Table II.
Sample selection during
the period 2002-2008
Islamic banks’
income structure
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banks with a ratio of net pro?t-loss-sharing income to net operating income higher
than the third quartiles Q
50
, with banks with the same ratio not exceeding the value of
the ?rst quartile (pro?t-loss-sharing lower than Q
25
). And we undertake the similar
comparison on the basis of the dependence to the nonpro?t-loss-sharing activities
(ratio of net Non_Pro?t-Loss-Sharing income to net operating income higher than Q
50
versus Non_Pro?t-Loss-Sharing lower than Q
25
).
5.2.1 Islamic bank risk and income structure. The results in Table IV show that
on the whole for Islamic banks in GCC countries, greater reliance on
pro?t-loss-sharing income is associated with higher risk and higher insolvency risk;
whereas higher dependence on nonpro?t-loss-sharing incomes implies to lower risk
levels.
5.2.2 Income structure and Islamic banks characteristics’. For further investigations
on the characteristics of banks in the high Islamic investment category and in the low
Islamic investment category income, Table V provides the results of the test performed
on the basis of our different Islamic income category. As a whole, banks with a larger
income share of pro?t-loss-sharing investments are less reliant than loans but are also
less leveraged (higher equity ratio), and they are more pro?table (higher ROA).
However, banks with a larger income share of nonpro?t-loss-sharing investments are
more reliant than loans, have less equity ratio and are less pro?table (lower ROA
and ROE).
5.3 Multivariate regression analysis
For further investigation about this issue that is based on risk and income structure of
Islamic banks in GCC countries, we conduct in this respect cross-section OLS
TA ROA ROE EQUITY LOANS PLS NON_PLS
Sample 1: non-listed and listed banks (42 banks)
Mean 3,040,000 5.43 14.08 40.88 44.73 19.07 42.80
SD 5,790,000 3.85 7.86 27.17 27.86 20.75 28.75
Min 23,000 0.68 3.53 10.34 0.91 0.49 0.07
Max 30,700,000 16.80 41.85 99.09 93.72 83.74 95.35
Sample 2: listed banks (24 banks)
Mean 4,730,000 4.50 15.59 28.87 51.10 16.45 45.10
SD 7,130,000 3.69 8.92 17.63 28.40 16.56 28.16
Min 402,000 0.68 3.53 10.34 3.15 2.27 0.07
Max 30,700,000 16.80 41.85 73.34 93.72 62.15 94.38
Sample 3: non-listed banks (18 banks)
Mean 811,000 6.43 11.51 56.11 33.97 22.89 38.11
SD 996,000 3.92 5.77 29.66 25.55 26.10 29.34
Min 23,000 0.93 3.67 11.44 0.91 0.49 0.55
Max 3,450,000 14.57 25.75 99.09 76.23 83.74 95.35
Notes: Signi?cant at:
*
10,
* *
5 and
* * *
1 percent levels; variables de?nitions (all variables are
expressed in percentage except TA expressed in thousand US$): LOANS – loans/total assets; equity –
equity/total assets; ROA – return on assets; ROE – return on equity; TA – total assets (thousand $);
PLS – net operating income from pro?t-loss-sharing arrangement/net operating income; NON PLS –
net operating income from other Islamic products than PLS products/net operating income
Table III.
Descriptive statistics for
GCC’s Islamic banks, on
average over the period
2002-2008 (percent)
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estimations on different samples of Islamic banks. More precisely, we regress the
accounting risk measures on different categories of Islamic banks’ product and of a set
of control variables.
The estimated models are:
M_RISK
i
¼ 1þbM_ISL
i
þ
X
¥
K
M_X
ki
þ1
i
where M_RISK
i
is the mean value, for bank i, taken for the period 2002-2008, of each
accounting based risk measure computed over the period (SDROA, SDROE, ADZ,
ADZP, ADZP1, ADZP2).
M_DIV I is the mean value, for bank
I
, for the period 2002-2008, of each category of
Islamic products variable (PLS and NON_PLS).
A large set of control variables was used initially. But because of frequent
collinearity among the variables, control variables are restricted to the natural
logarithm of total assets LOG (TA), loans to total assets (LOANS), ROE and the
leverage ratio orthogonalized with total assets (EQUITY). We also include the
annual growth rate of total assets (DTA). As well as, we include the ratio Islamic banks
assets to total banks assets ratio (Cont_C) to control the country speci?c
characteristics.
Table VI shows the results obtained from regression analysis. We have separated
estimations from listed Islamic banks and non-listed Islamic banks. In all accounting
data based estimation; higher pro?t-loss-sharing activities are associated with an
increase in Islamic bank defaults risk (SDROA, SDROE, and ADZ). The coef?cient
associated to the assets growth variable MDTA is signi?cant and negative in most
of estimations with risk measures.
To cheek for robustness and to explore the effect of a relatively larger expansion into
pro?t-loss-sharing investments and non pro?t-loss-sharing investments on risk, we ran
our estimations by including dummies for diversi?cation quintiles Q
50
and Q
25
instead
Risk measures Insolvency risk measures
SDROA SDROE ADZ ADZP ADZP1 ADZP2
PLS . Q
50
Mean 0.0648 0.1183 25.542 15.264 1.458 13.806
PLS , Q
25
Mean 0.0197 0.0606 40.327 35.440 3.938 31.501
t-statistic of the mean test 2.580
* *
1.781
*
20.639 21.752
*
22.586
* *
21.471
*
NON_PLS . Q
50
Mean 0.0180 0.062 29.530 25.697 2.775 22.921
NON_PLS , Q
25
Mean 0.0399 0.099 19.104 24.957 2.988 21.969
t-statistic of the mean test 21.968
*
21.775
*
1.199 0.081 20.285 0.112
Notes: Signi?cant at:
*
10,
* *
5 and
* * *
10 percent levels for a bilateral test, respectively; t-statistics test
for the null: “risk/insolvency is not different for higher level of PLS and NON_PLS product”; variables
de?nitions: PLS – ratio of net PLS operating income to net operating income; NON_PLS – ratio of net
NON_PLS operating income to net operating income; SDROA – standard deviation of the return on
average assets; SDROE – standard deviation of the return on the average equity; ADZ – Z-score;
ADZP – “ZP-score”; ADZP1 – measure of bank portfolio risk; ADZP2 – measure of leverage risk
Table IV.
Income structure and
accounting indicators of
risk for Islamic banks in
GCC (2002-2008)
Islamic banks’
income structure
235
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Table V.
Income structure and
Islamic bank
characteristics for Islamic
bank in GCC countries
(2002-2008)
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Risk measures Insolvency measures
SDROA SDROE ADZ ADZP ADZP1 ADZP2
Sample 1: all banks (42)
M_NON_PLS 20.001 0.02 0.38 5.019 0.71 4.38
(t-statistics) (20.05) (20.44) (0.81) (0.35) (0.35) (0.34)
M_PLS 0.109 0.262 0.99 1.92 2.65 1.65
(t-statistics) (3.14
* * *
) (3.39
* * *
) (21.47) (0.91) (20.91) (20.91)
M_LOG(TA) 0.002 0.006 0.06 1.04 0.144 0.901
(t-statistics) (0.89) (20.90) (0.9) (0.44) (0.44) (0.44)
M_ ROE 0.046 0.423 1.09 2.06 3.02 1.76
(t-statistics) (0.63) (2.97
* *
) (20.72) (0.47) (0.49) (0.46)
MD TA 20.0002 0.0006 0.06 0.0005 0.0006 0.0005
(t-statistics) (21.41) (22.16
* *
) (0.9) (0.01) (0.00) (0.01)
M_EQUITY 0.095 0.023 1.18 3.16 4.41 2.72
(t-statistics) (3.02
* * *
) (0.31) (1.57) (1.35) (1.36) (1.35)
LOANS 0.025 0.035 0.33 0.455 0.08 0.90
(t-statistics) (0.89) (0.66) (0.62) (0.03) (0.03) (0.44)
Cont_C 0.0009 0.0007 0.003 0.03 0.004 0.025
(t-statistics) (0.65) (0.32) (21.49) (20.41) (20.41) (20.40)
R
2
46.71 40.8 26.83 18.46 18.53 18.45
Sample 2: listed banks (24)
M_NON_PLS 0.023 21.36 20.967 20.164 0.0012 20.165
(t-statistics) (1.56) (21.59) (22.61
*
) (20.60) (0.07) (0.63)
M_PLS 0.65 0.265 20.14 20.405 20.527 20.399
(t-statistics) (3.37
* * *
) (2.51
* *
) (20.27) (1.17) (22.07
*
) (21.08)
M_LOG(TA) 0.402 0.0038 0.12 20.58 20.0016 0.006
(t-statistics) (0.87) (0.39) (0.86) (21.64) (20.68) (0.2)
M_ROE 0.24 0.455 21.375 21.05 0.038 21.24
(t-statistics) (6.53
* * *
) (5.18
* * *
) (21.89
*
) (22.82
* *
) (0.79) (22.76
* *
)
MD TA 20.07 20.03 0.047 0.0034 0.0015 0.002
(t-statistics) (23.33
* * *
) (21.06) (0.84
* *
) (0.10) (0.57) (0.06)
M_EQUITY 0.11 0.917 0.892 0.122 20.017 0.21
(t-statistics) (5.12
* * *
) (0.06) (1.24) (20.47) (0.50) (0.27)
LOANS 20.002 20.195 0.203 0.104 0.0167 0.002
(t-statistics) (0.27) (0.03) (0.76) (0.53) (1.28) (0.31)
Cont_C 20.115 21.5 1.34 0.21 0.005 0.21
(t-statistics) (1.65) 23.8 (1.23) (0.27) (0.11) (0.22)
R
2
91.6 40.72 37.16 45.27 39.13 12.59
Sample 3: non-listed banks (18)
M_NON_PLS 0.26 0.342 20.814 0.85 0.47 0.802
(t-statistics) (1.10) (0.82) (0.002) (0.98) (0.51) (2.41
*
)
M_PLS 0.27 0.39 0.96 2.35 1.15 2.20
(t-statistics) (2.07
* * *
) (1.89
*
) (23.02
* * *
) (22.30) (1.41) (1.03)
M_LOG(TA) 0.030 0.054 0.016 0.115 0.64 0.109
(t-statistics) (0.55) (0.55) (0.01) (0.66) (0.34) (0.70)
M_ROE 0.63 0.001 0.61 0.06 20.42 20.006
(t-statistics) (20.07) (0.17) (0.34) (23.79
* * *
) (2.26) (3.98
* *
)
MD TA 0.0395 0.041 0.15 0.85 22.78 0.36
(t-statistics) (20.15) (0.55) (20.04) (2.81
* *
) (1.81) (22.85)
M_EQUITY 0.89 1.17 2.43 0.439 0.27 4.11
(t-statistics) (1.15) (0.86) (0.01) (1.6) (0.93) (21.68)
LOANS 0.67 0.78 4.39 20.05 0.57 27.96
(continued)
Table VI.
OLS estimations for a
sample of 42 Islamic
banks with M_PLS and
M_NON_PLS as the
independent variables
Islamic banks’
income structure
237
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of the values of pro?t-loss-sharingandnonpro?t-loss-sharing. Table VII shows the results
for the broad sample, for listedIslamic banks andfor non-listedIslamic banks. Overall, we
?nd that greater reliance on pro?t-loss-sharing investment is associated with higher risk
and higher default (insolvency) risk. Hence, Islamic banks which more than 50 percent of
their income comes frompro?t-loss-sharing ?nancing are faced to a higher riskthanthose
banks with less of 25 percent of the income come from pro?t-loss-sharing.
6. Discussion and conclusion
The purpose of this study is analyzing the risk implication on the ?nancial Islamic
products presented by Islamic bank in GCC countries. Our study shows that Islamic
banks expanding into pro?t-loss-sharing products present higher risk and higher
insolvency risk than banks which invest less in this kind of arrangement. As we have
listed bank prefers to invest less in nonpro?t-loss-sharing products than
pro?t-loss-sharing products. This attitude can be explained by the fact that Islamic
banks focus more on the ?nancial stability of their investments. In fact, Islamic banks as
an equity-based capital structure dominated by shareholders equity and investment
deposit holders have to offer a competitive remuneration to them especially to the
deposit holders. Indeed, in a competitiveness ?nancial market like the GCC market,
customer will be more sensitive to the volatility of returns offered on investment deposit
and may withdraw their funds in case of low remuneration. As a result, Islamic banks
have to absorb the losses, if it is the case, to make sure that the investment deposit
holders received a rate of return equivalent to the rate offered in the market. Therefore, to
manage their displaced commercial risk, Islamic banks prefer to invest more inless risky
investment (nonpro?t-loss-sharing) than pro?t-loss-sharing products to guarantee the
level of remuneration of its deposit holders. Islamic banks are strongly exposed to
massive withdrawal risk due to lower rate of return on investments deposits which
threaten the position of the bank. Depositors can at any time withdrawtheir deposit fund
to another ?nancial institution that gives higher remuneration.
Future researches have to study the relationship between the capital and the
deposits structures of Islamic banks and risks.
Risk measures Insolvency measures
SDROA SDROE ADZ ADZP ADZP1 ADZP2
(t-statistics) (0.88) (0.58) (0.03) (21.36) (1.77) (2.93)
Cont_C 1.67 2.5 5.94 0.39 10.54 13.3
(t-statistics) (21.03) (21.29) (0.06) (22.74
* *
) (2.53) (22.85)
R
2
74.26 61.95 52.36 79.83 56.94 81.31
Notes: Signi?cant at:
*
10,
* *
5 and
* * *
10 percent levels, respectively; t-statistics are corrected for
heteroskedasticity following White’s methodology; variable de?nition: M_X – mean of the variable X
for bank i over the period 2002-2008; LOG (TA) – logarithm for total assets for bank I; ROE – return
on average equity; MDTA – annual growth rate for total assets; equity ¼ equity orthogonalized with
TA; LOANS – loans/total assets; PLS – ratio of net PLS operating income to net operating income;
NON_PLS – ratio of net NON_PLS operating income/net operating income; Cont_C – ratio Islamic
banks assets to total banks assets ratio for each country; SDROA – standard deviation of the return
on average assets; SDROE – standard deviation of the return on the average equity; ADZ – Z-score;
ADZP – “ZP-score”; ADZP1 – measure of bank portfolio risk; ADZP2 – measure of leverage risk
Table VI.
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Risk measures Insolvency measures
SDROA SDROE ADZ ADZP ADZP1 ADZP2
Sample 1: all banks (42)
D_PLS Q
50
0.0095 0.013 0.018 1.605 0.22 21.37
(t-statistics) (3.13
* *
) (3.35
* * *
) (1.73
*
) (20.10) (20.10) (20.10)
D_PLS Q
25
0.011 20.033 0.512 0.736 1.01 6.35
(t-statistics) (0.61) (0.36) (1.37) (0.58) (0.58) (0.58)
D_NON_PLS Q
50
(0.041 0.122 0.31 0.409 0.55 0.323
(t-statistics) (21.28) (23.6
* * *
) (0.75) (0.28) (0.28) (0.17)
D_NON_PLS Q
25
0.045 0.132 0.3 0.372 0.49 0.349
(t-statistics) (22.15
* *
) (2.54
* *
) (0.46) (0.17) (0.16) (20.10)
M_LOG(TA) 0.0004 0.011 0.054 0.75 0.103 0.655
(t-statistics) (0.28) (21.68) (0.67) (0.28) (0.27) (0.28)
M_ROE 0.032 0.205 0.59 0.45 0.655 3.9
(t-statistics) (20.28) (1.47) (20.34) (0.78) (0.80) (0.77)
M_D TA 0.0004 0.0004 0.05 0.00047 0.006 0.00047
(t-statistics) (21.12) (21.58) (0.65) (20.04) (20.04) (20.04)
M_EQUITY 0.038 0.037 1.26 0.32 0.455 2.83
(t-statistics) (1.06) (20.65) (1.75
*
) (1.35) (1.35) (1.35)
LOANS 0.005 0.007 0.44 0.097 0.141 0.847
(t-statistics) (0.19) (0.16) (0.75) (20.05) (0.05) (20.05)
CONT_C 0.0003 0.0003 0.0049 0.044 0.006 20.038
(t-statistics) (0.28) (1.6) (21.98
*
) (20.53) (0.27) (0.053)
R
2
49.31 62.84 41.72 17.04 24.85 17.06
Sample 2: listed banks (22)
D_PLS Q
50
0.0095 0.157 0.167 0.08 20.015 20.085
(t-statistics) (2.17
* *
) (3.08
* * *
) (21.88
*
) (0.73) (20.418) 0.098
D_PLS Q
25
0.006 0.0301 20.097 0.179 0.013 (20.84)
(t-statistics) (0.88) (0.73) (20.68) (1.97
*
) (1.79
*
) (1.88
*
)
D_NON_PLS Q
50
0.0015 0.084 0.212 0.149 0.010 0.139
(t-statistics) (0.16) (0.20) (0.91) (1.61) (1.32) (1.57)
D_NON_PLS Q
25
0.017 0.026 20.22 0.132 20.0102) 20.122
(t-statistics) (1.2) (0.78) (21.67) (21.57) (21.52) (21.52)
M_LOG(TA) 0.014 0.012 0.036 0.048 0.003 0.0375
(t-statistics) (1.15) (1.57) (0.66) (1.41) (1.07) (1.38)
M_ROE 0.27 0.338 22.54 21.53 0.050 21.48
(t-statistics) (6.55
* * *
) (4.6
* * *
) (22.98
* * *
) (22.84
* *
) (21.11) (22.85
* * *
)
M_D TA 20.0103 20.0002 0.014 0.0489 0.0004 0.045
(t-statistics) (21.95
*
) (23.75
* * *
) (2.56
* *
) (1.41) (0.47) (1.37)
M_EQUITY 0.078 0.234 20.49 0.742 0.033 0.708
(t-statistics) (2.79
* *
) (1.51) (0.85) (2.03
* *
) (1.1) (2.01
* *
)
LOANS 0.0009 0.062 0.176 20.008 0.0085 20.01641
(t-statistics) (0.09) (1.68) (20.80) (20.06) (0.47) (20.12)
Cont_C 0.007 2.05 0.266 0.197 0.012 0.18
(t-statistics) (20.18) (20.08) (0.31) (0.36) (0.26) (0.35)
R
2
83.52 20.01 49.62 50.06 44.38 48.76
Sample 3: non-listed banks (18)
D_PLS Q
50
0.045 0.103 0.59 0.065 0.59 0.80
(t-statistics) (3.11
* *
) (2.87
* *
) (4.09
* * *
) (4.8
* * *
) (4.09
* * *
) (4.8
* * *
)
D_PLS Q
25
0.045 0.094 0.25 0.029 0.25 0.34
(t-statistics) (0.93) (1.42) (22.11
*
) (2.48
*
) (2.11) (2.36
*
)
D_NON_PLSQ
50
0.027 0.005 0.137 0.002 0.137 0.026
(continued)
Table VII.
OLS estimations for
Islamic banks with
dummies variables on the
structure of income as the
independent variables
(cross-section estimation)
Islamic banks’
income structure
239
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Note
1. Moody investor service, 2009.
References
Bank of Sudan (2001), Annual Report, Bank of Sudan, Khartoum.
Boyd, J. and Graham, S. (1986), “Risk, regulation, and bank holding company expansion”, Federal
Reserve Bank of Mineapolis, Quarterly Review, Spring.
Chang, B. and Liu, M. (2009), “Islamic banking: interest-free or interest-based?”, Paci?c-Basin
Finance Journal, Vol. 17, pp. 125-44.
Chapra, M.U. (1997), Vers un syste `me Mone´taire juste, Ed Islamic Research and Training
Institute, Jeddah.
Dar, H.A. and Presley, J.R. (2000), “Lack of pro?t loss sharing in Islamic banking:
management and control imbalances”, International Journal of Islamic Financial
Services, Vol. 2, pp. 2-9.
DeYoung, R. and Roland, K. (2001), “Product mix and earnings volatility at commercial banks:
evidence from a degree of total leverage model”, Journal of Financial Intermediation,
Vol. 10, pp. 54-84.
Risk measures Insolvency measures
SDROA SDROE ADZ ADZP ADZP1 ADZP2
(t-statistics) (0.43) (20.05) (0.71) (0.16) (0.71) (0.12)
D_NON_PLS Q
25
0.02 0.06 0.098 0.005 0.098 0.06
(t-statistics) (0.69) (1.05) (20.84) (20.49) (20.84) (20.44)
M_LOG(TA) 0.013 0.016 20.0177 0.017 0.032 0.19
(t-statistics) (0.32) (20.24) (20.4) (21.49) (20.26) (21.35)
M_ROE 0.10 0.06 0.87 0.007 0.871 1.13
(t-statistics) (20.32) (0.14) (20.98) (0.08) (20.98) (21.05)
M_D TA 0.004 0.016 0.02 0.007 0.02 0.03
(t-statistics) (0.15) (0.24) (0.25) (20.10) (0.25) (20.38)
M_EQUITY 0.095 0.17 1.48 0.07 1.48 1.099
(t-statistics) (0.24) (20.28) (1.33) (0.67
* *
) (1.33) (0.83)
LOANS 0.102 0.37 2.09 0.209 0.209 2.65
(t-statistics) (20.4) (0.91) (2.98
* * *
) (2.97
* *
) (2.89
*
) (3.04
* *
)
Cont_C 4.98 6.16 3.35 3.27 3.35 3.62
(t-statistics) (20.56) (20.44) (0.13) (1.34) (0.13) (1.2)
R
2
64.69 56.93 58.92 74.58 98.29 74.48
Notes: Signi?cant at:
*
10,
* *
5 and
* * *
10 percent levels, respectively; t-statistics are corrected for
heteroskedasticity following White’s methodology; variable de?nition: M_X – mean of the variable X
for bank i over the period 2002-2008; LOG (TA) – logarithm for total assets for bank I; ROE – return
on average equity; TA – annual growth rate for total assets; equity – equity orthogonalized with TA;
LOANS – loans/total assets; Cont_C – ratio Islamic banks assets to total banks assets ratio for each
country; D-PLSQ
50
/D_NON_PLSQ
50
– dummy variable which takes the value of 1 when PLS/NON_
PLS for bank I is greater than the third quartile of overall sample and 0 otherwise; D-PLSQ
25
/D_NON_
PLSQ
25
– dummy variable which takes the value of 1 when PLS /NON_PLS for bank I is lower than
the ?rst quartile of overall sample and 0 otherwise; SDROA – standard deviation of the return on
average assets; SDROE – standard deviation of the return on the average equity; ADZ – Z-score;
ADZP – “ZP-score”; ADZP1 – measure of bank portfolio risk; ADZP2 – measure of leverage risk Table VII.
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Goyeau, D. and Tarazi, A. (1992), “E
´
valuation du risque de de´faillance bancaireen Europe”,
Revue d’Economie Politique, Vol. 102 No. 2, pp. 249-80.
Ibrahim, B.E. (2006), “The ‘missing links’ between Islamic development objectives and the
current practice of Islamic banking – the experience of the Sudanese Islamic banks (SIBs)”,
Humanomics, Vol. 22 No. 2, pp. 55-66.
International Monetary Fund (2009), World Economic and Financial Survey, Regional Economic
Outlook, Middle East and Central Asia, October.
Kuran, T. (1995), “Islamic economics and the Islamic sub economy”, Journal of Economic
Perspectives, Vol. 4, pp. 155-73.
Lepetit, L., Nys, E., Rous, P. and Tarazi, A. (2007), “Bank income structure and risk: an empirical
analysis of European banks”, Journal of Banking & Finance, Vol. 32, pp. 1452-67.
Lewis, M.K. (2007), “Islamic banking in theory and practice”, Monish Business Review, Vol. 3,
pp. 1-8.
Matoussi, H. and Grassa, R. (2010), “Investment portfolio and Islamic banks’ performance:
evidence from the GCC countries”, paper presented at The 11th Mediterranean Research
Meeting, Florence, March.
Mills, P.S. and Presley, J.R. (1999), Islamic Finance: Theory and Practice, Macmillan, Basingstoke.
Presley, J.R. (1988), Directory of Islamic Financial Institutions, Croom Helm, Beckenham.
Roy, D.A. (1991), “Islamic banking”, Middle Eastern Studies, Vol. 27, pp. 427-56.
Siddiqui, M.N. (2004), Riba, Bank Interest and the Rational of It Prohibition, ed Islamic Research
and Training Institute, Jeddah.
Stiroh, K. and Rumble, A. (2006), “The dark side of diversi?cation: the case of US ?nancial
holding companies”, Journal of Banking & Finance, Vol. 30, pp. 2131-61.
Sudin, H. (1996), “The effects of management policy on the performance of Islamic banks”, Asia
Paci?c Journal of Management, Vol. 13 No. 2, pp. 63-76.
Suleiman, N.M. (2000), Corporate governance in Islamic banks, Islamic Banking, London,
pp. 98-116.
Further reading
Dar, H.A. and Presley, J.R. (1991), “Islamic ?nance: a Western perspective”, International Journal
of Islamic Financial Services, Vol. 1, pp. 1-9.
Stiroh, K. (2004), “Diversi?cation in banking: is non-interest income the answer”, Journal of
Money, Credit and Banking, Vol. 36, pp. 853-82.
Corresponding author
Rihab Grassa can be contacted at: [email protected]
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Islamic banks’
income structure
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This article has been cited by:
1. Rihab Grassa. 2015. Corporate governance and credit rating in Islamic banks: Does Shariah governance
matters?. Journal of Management & Governance . [CrossRef]
2. Rim Ben Selma Mokni, Abdelghani Echchabi, Dhekra Azouzi, Houssem Rachdi. 2014. Risk management
tools practiced in Islamic banks: evidence in MENA region. Journal of Islamic Accounting and Business
Research 5:1, 77-97. [Abstract] [Full Text] [PDF]
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doc_949109901.pdf
The purpose of this paper is to analyze the income structure of Islamic banks in the Gulf
Cooperation Council (GCC) countries and to explore the effect of the diversification of banks’ earning
on risks that may harm these latter.
Accounting Research Journal
Islamic banks' income structure and risk: evidence from GCC countries
Rihab Grassa
Article information:
To cite this document:
Rihab Grassa, (2012),"Islamic banks' income structure and risk: evidence from GCC countries", Accounting
Research J ournal, Vol. 25 Iss 3 pp. 227 - 241
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Islamic banks’ income structure
and risk: evidence from GCC
countries
Rihab Grassa
University of Manouba, Tunis, Tunisia
Abstract
Purpose – The purpose of this paper is to analyze the income structure of Islamic banks in the Gulf
Cooperation Council (GCC) countries and to explore the effect of the diversi?cation of banks’ earning
on risks that may harm these latter.
Design/methodology/approach – Using data from 2002-2008 for 42 Islamic banks, this article
provides descriptive and analytical analysis and multiple regression equations.
Findings – This article reveals that greater reliance on the income share of the pro?t-loss-sharing
products is associated with higher risk and higher insolvency risk for both listed Islamic banks and
non-listed Islamic banks. However, no effect has been observed between the operation income of
non-pro?t-losses-sharing products and risk levels. That is why listed banks prefer to invest less in
non-pro?t-loss-sharing products than in pro?t-loss-sharing products.
Research limitations/implications – Financial regulators in emerging Islamic ?nancial market
should help Islamic banks to ?nd equilibrium between the expansion of the Islamic ?nancial market
and respect for the raison d’e ˆtre of Islamic ?nance: the pro?t and loss sharing mechanisms.
Originality/value – To the best of the author’s knowledge, this is the ?rst article that empirically
tests why Islamic banks prefer to invest less in pro?t-loss-sharing products. Also, this article
contributes to studying the relationship between Islamic ?nance and risk.
Keywords Saudi Arabia, Kuwait, United Arab Emirates, Qatar, Bahrain, Islam, Banks, Islamic banks,
Risk management, Performance, Pro?t-loss-sharing products
Paper type Research paper
1. Introduction
Today Islamic banking system in Gulf Cooperation Council (GCC) countries is facing
many changes in the form of increased competitions in the ?nancial market,
concentration and restructuring. Islamic banks have reacted to the new environment of
the ?nancial market by adopting a proactive strategy by diversifying the range of
Islamic ?nancing products offered to their customers. These changes have mainly lead
Islamic banks to diverge from their classical pro?t losses sharing ?nancing scheme to
another ?nancing system that presents more advantages for them. Hence, an important
share of pro?t and losses sharing ?nancing products has been given to non-pro?t and
losses sharing products. As a result, the structure of the bank income experienced
a dramatic change.
Most of the existing studies focusing on the portfolio diversi?cation effect explored
the Western context and more especially the conventional-banking system. However,
no articles have studied empirically the portfolio diversi?cation effect of the Islamic
?nancial system.
The purpose of this paper is to evaluate the risk implications of the diversi?cation
structure of Islamic banks in GCC countries which has shifted away from
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1030-9616.htm
Islamic banks’
income structure
227
Accounting Research Journal
Vol. 25 No. 3, 2012
pp. 227-241
qEmerald Group Publishing Limited
1030-9616
DOI 10.1108/10309611211290185
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pro?t-losses-sharing activities to others nonpro?t-loss-sharing activities but
also permitted by Shari’a scholars to discuss the way of such behavior. Through
using a sample of Islamic bank data from 2002 to 2008 for 42 Islamic banks, we start
by the output diversi?cation that is measured by two indicators, the income share of
(i) pro?t-loss-sharing income and the nonpro?t-loss-sharing income of (ii). In the
beginning, we start by comparing the risk level of Islamic banks which use more
pro?t-loss-sharing ?nancing method with the risk level of Islamic banks which have
preferred to invest more in nonpro?t-loss-sharing ?nance. Our ?ndings show that
higher reliance on pro?t-loss-sharing ?nancing activity is strongly associated with
higher risk, and our study shows that Islamic banks expanding into pro?t-loss-sharing
products present higher risk and higher insolvency risk than banks which invest less
in this kind of arrangement. Additionally, listed bank prefer to invest less in
nonpro?t-loss-sharing products than pro?t-loss-sharing products. This behavior can be
explained by the fact that Islamic banks focus more on the ?nancial stability of their
investments. Islamic banks as an equity-based capital structure dominated by
shareholders equity and investment deposit holders have to offer a competitive
remuneration to them especially to the deposit holders. Indeed, in a competitiveness
?nancial market like the GCC market, customer will be more sensitive to the volatility of
returns offered on investment deposit and may withdraw their funds in case of low
remuneration.
The article proceeds as follows: in Section 2, we review the following studies about
pro?t-loss-sharing paradigm and Islamic banks attitudes, studies about bank risk and
product diversi?cation and we show how our study extends the existing work about
Islamic ?nance. In Section 3, we present a description of the context of our study.
In Section 4, we reveal the methodology adopted in this paper. In Section 5 we present
and discuss the results of our regression analysis. Finally, in Section 6 we summarize
the ?nding of the paper.
2. Literature review: pro?t-loss-sharing paradigm and Islamic banks
attitude
Islamic ?nance is based on Quran law that forbids all form of interest and especially
interest charging on loan (Roy, 1991). The hostility towards the interest is based on the
belief that the Islamic religious book forbids all forms (Kuran, 1995). In fact, one of the
most important instructions of Islam to establish justice and eliminate immoral
exploitation in commercial transactions is the prohibition of all sources of “unfair
enrichment” (Chapra, 1997). As a matter of fact, the Islamic holy book considers “Riba”
(usury) as one of the sources of unjust enrichment. According to Shari’a, the riba
banned by Islam refers to the “premium” to be paid by the borrower or to the lender
in addition to the principal amount as a condition to the credit or the extension of its
maturity. In other word, it is the addition in the amount of the principal of a loan
according to the time and the amount of the loan (Suleiman, 2000). In this sense, riba
has the same meaning and is considered as an interest form (Chapra, 1997).
However, Islam distinguishes between money and capital. To transform money to
capital there is a need for an enterprise application. Consequently, there is the risk
taking and the required knowledge to bring factors of production jointly in order to
generate return (Presley, 1988). If the lender provides project in any form, he has to
justify a pro?t (or loss) share, but not a ?xed or a certain return; the prize. That is to say,
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the pro?t share is determined by contribution in terms of enterprise. So, the relationship
between creditor/debtor that we can see in conventional economy is rede?ned in Islam.
The creditor becomes a partner in the project, not distanced from the use in which
his money is employed. Indeed, Islamic economic perspective distinguishes the “rate of
interest” fromthe “rate of return”. On the one hand, Islamundoubtedly forbids receiving,
payment and trading with charging interest and on the other hand, it encourages trade.
Indeed, inthe interest-free system(the Islamic system), people are able to earna returnon
their money just by subjecting themselves to the risk involved in pro?t sharing. Since
the use of interest rates in ?nancial transactions is banned and the partnership is
encouraged, Islamic scholars think that banks should undertake operations only on the
basis of “pro?ts and loss sharing” arrangements or other acceptable modes of ?nancing.
That is why; the idea of Islamic bank came into surface. Islamic banks are ?nancial
institutions that are expected to undertake operations only on the basis of pro?t and loss
sharing arrangements or other “acceptable” means of ?nancing by Shari’a. In this
context, the relationship between creditor/debtor that we can observe in conventional
economy is rede?ned and the creditor becomes a partner in the project by sharing the
pro?t, supporting the losses and sharing the risks (Siddiqui, 2004; Dar and Presley, 2000;
Sudin, 1996; Lewis, 2007). So, Islamic bank is a ?nancial institution that receives
deposits and carries all banking activities except operations of lending and interest
based activities. The banks’ liabilities are constituted by all mobilized founds through
Mudaraba operation. Bank assets are formed by all advanced funds used in
pro?t-loss-sharing’ based techniques or all other operations permitted by the Islamic
law. An Islamic bank is a ?nancial intermediary mobilizing savings from the public on
Mudaraba basis and advancing capital to entrepreneurs on the same basis
(Suleiman, 2000).
Most theoretical models of Islamic banking are based on the Mudaraba
(pro?t-sharing) and/or Musharaka ( joint venture) concepts of pro?t-loss-sharing
(Dar and Presley, 2000). However, most of Islamic banks use other ?nancing contracts
that are permissible in Islam but not strictly pro?t-loss-sharing in nature. Such
?nancing contracts may be based on Murabaha (cost plus), Ijarah (leasing), Bai’ muajjal
(deferred payment sale), Bai’Salam (forward sale), and Istisna (contract manufacturing)
concepts.
During the last decade, many researches ?nd that Islamic banking, as it is practiced
today, tends to deviate substantially from the pro?t-loss-sharing paradigm. Ibrahim
(2006) ?nds that 34 percent of the investments of the Sudanese’s’ Islamic banks are a
pro?t-loss-sharing investments. However, nonpro?t-loss-sharing investments are
nearly 50 percent. Sudan’s bank explains this attitude in its Annual Report of 2001,
that the substantial use of other mode of ?nancing than pro?t-loss-sharing mode,
especially Murabaha, in Sudanese banking system is due to “the simplicity of this
mode and the people’s preference” (Bank of Sudan, 2001). While, Yusuf (1996) ?nds
that during the period 1980-1990, the share of the pro?t-loss-sharing investments were
in the range of 33 and 38 percent for Iranian banks and in the range, the
nonpro?t-loss-sharing techniques shared around 51-60 percent for Iranian banks.
Chang and Liu (2009) ?nds that, in Malaysian context pro?t-loss-sharing products
represented only 0.5 percent of the total ?nancing offered by Islamic banks in Malaysia
however Murabaha represented 49.9 percent Islamic bank ?nancing in Malaysia, in
practice, is still based largely on nonpro?t-loss-sharing modes of ?nancing that
Islamic banks’
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are permissible under the Shari’ah whereas, Matoussi and Grassa (2010) ?nd that
during the period 2002-2008, on average, the share of the nonpro?t-loss-sharing
?nancing on the total ?nancing made by Islamic banks in GCC countries is
85.27 percent and generates 70 percent of the income of Islamic banks income.
However, only 14.73 percent Islamic banks ?nancing in GCC countries was
pro?t-loss-sharing ?nancing and generate 30 percent of the total Islamic banks income
in GCC countries.
The small share allocated by Islamic banks to the pro?t-loss-sharing ?nancing even
the high return of these products, can be explained by the fact that pro?t-loss-sharing
?nancing products are more risky, require more costly monitoring and encounter
several inconveniences due to the lack of management and control right. In fact,
Musharaka ?nancing encounters moral hazard problems associated with ex post
information asymmetry, the entrepreneur (borrower); for example has an incentive to
under-declare or arti?cially reduce reported pro?t (Mills and Presley, 1999). Besides, in
the case of Mudaraba contract, the entrepreneur has an incentive to undertake
high-risk projects because the entrepreneur is actually given a call option whereby he
or she gains on the upside but bears no losses at all on the downside. Also, in
Mudaraba ?nancing, the bank provides all the risk associated with the capital, but the
management and control of the project are mostly in the hands of the entrepreneur.
This think accentuates the principal-agent problems associated with
pro?t-loss-sharing ?nancing (Dar and Presley, 2000). Nevertheless, Ibrahim (2006)
explains the lower percentage of pro?t-loss-sharing investment by the fact that non
pro?t-loss-sharing ?nancing contract satis?es the need of the majority customer of the
bank more than pro?t-loss-sharing ?nancing mode.
Most of the studies explained theoretically the relationship between Islamic
?nancial products and the risk taking by Islamic banks. However, to our knowledge,
there are no researches that tried to explore this subject empirically. As well, little
studies have focused on the effect of the bank income structure on risk taking. Most of
them focus on the conventional ?nancial context. DeYoung and Roland (2001)
concludes that fee-based activities increase the volatility of banks revenue in the USA.
Stiroh and Rumble (2006) ?nd similar results for US ?nancial holding companies
observed during the period 1997-2002. Lepetit et al. (2007) ?nd that European banks
expanding into non-interest income activities present higher risk and higher
insolvency risk than banks mainly supply loans. However, no article has studied the
effect of the diversi?cation of the Islamic banks’ earning on risks.
This paper tries to explore the effect of the earning diversi?cation on the Islamic
banks’ risk. Hence, to our knowledge, this is the ?rst study that explores the impact of
the diversi?cation of Islamic banks’ earning on risk in the case of GCC countries.
In the next section, we will present the methodology adopted in this research and the
context of our study.
3. Context of study: Islamic banking in GCC countries
The GCC consists of six countries located in the Middle East: Saudi Arabia, Kuwait,
United Arab Emirates, Qatar, Oman and Bahrain. The GCC was founded in 1981 with
the objective of coordinating policies of various political, economic, and social matters,
and have similar regulations. The GCC countries are independent governments with
independent currencies. Oil, which is the main commodity of these countries, was
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discovered in the 1940s in GCC countries and constitutes today the world’s largest
reserve. Banking industry development in GCC countries is linked to oil export.
Since the oil boom of the 1970s, foreign banks are installed in GCC countries. Early
banking in the GCC region experienced a lot of foreign ownership mostly by a bank
named British Bank in the Middle East. This bank had branches across all six GCC
countries. Other foreign banks were also popular as there were large revenues from oil
trade. Local banks were not common because of lack of suf?cient experience. Since
1975, the Islamic bank industry was developed in GCC. The ?rst Islamic banks
implanted in GCC countries were the Kuwait Finance House, Dubai Islamic Bank and
Al-Rajhi bank in Saudi Arabia. The GCC region currently remains the primary
?nancier of Islamic ?nance world-wide. By the end of 2008, there were more than
45 Islamic banks in GCC, which used to offer a full range of Islamic banking products
and services. Today, the GCC countries are widely believed to have the most developed
Islamic ?nancial system in the world that operates side-by-side with a
conventional-banking system. A part from the interest-free banking scheme, the
GCC countries have a well-developed Islamic interbank money market, Islamic
securities market, and Islamic insurance market.
Seeing the signi?cant growth of the Islamic ?nance, several GCC countries have
installed a comprehensive prudential and reporting framework, tailor-made for the
speci?c concepts and needs of Islamic banking and insurance. In addition to the
numerous Islamic ?nancial institutions active in its ?nancial sector, GCC countries also
presented as a host to a number of organizations based on the development of Islamic
?nance, including:
.
The Accounting and Auditing Organization for Islamic Financial Institutions
(AAOIFI).
.
The Liquidity Management Centre (LMC).
.
The International Islamic Financial Market (IIFM).
.
The Islamic International Rating Agency (IIRA).
Today, Gulf Islamic banks control a market share with about 15 percent of the regional
banking system’s assets, and have become part of mainstream ?nancial intermediation
in this part of the world. At the same time, Islamic banks in the GCC have also become
more diverse: large pioneers established in the 1970s co-exist with new entrants, former
conventional ?nancial institutions recently converted into fully ?edged
Shari’ah-compliant banking entities and the Islamic windows of still-conventional
banking providers. The total assets of Islamic banks in GCC exceed 125 billion $ (more
than 25 percent Shari’ah-compliant banking assets globally)[1].
According to the International Monetary Fund (October 2009), during the period
2002-2008, in the average, Gulf Islamic banks’ assets represent 23.8 percent of the total
banking assets, and the growth rate of Islamic banks’ assets is over 44 percent (the
growth rate of assets of the global banking system in GCC is over 22.6 percent). Table I
summarizes some data for each GCC country.
4. Methodologies
In this research, we will adopt the methodology used by Stiroh and Rumble (2006) and
Lepetit et al. (2007). We will provide, as well, some modi?cations to adapt the empirical
Islamic banks’
income structure
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model to the particularities of Islamic banks. That is why; we will have three kinds of
variables: Islamic products variables, accounting data based risk measures variables
and control variables.
4.1 De?nitions of variables, data and primary statistics
4.1.1 Islamic products variables: Islamic banks’ income structure. In this research, we
are interested only in Islamic products incomes and we will not take into consideration
the other incomes earned by Islamic banks like commission, transaction fee, etc.
To measure Islamic banks products, we distinguish two components of Islamic
?nancial products income: pro?t-loss-sharing products income (PLS income) and
nonpro?t-loss-sharing products income (Non_PLS income). Hence, we de?ne a ratio of
net PLS income to net operating income (PLS) and a ratio of net Non_PLS income to net
operating income (NON_PLS). Net PLS operating income is equal to PLS income minus
PLS operating expense and net Non_PLS income is equal to Non_PLS income minus
Non_PLS operating expense.
4.1.2 Accounting data based risk measures. In this study, we used two standards of
risk measurement, based on annual accounting data and determined for each bank
throughout the period:
.
the standard deviation of the return on average assets (SDROA); and
.
the standard deviation of the return on average equity (SDROE).
We also compute insolvency risk measures:
(1) The “Z-score” (ADZ) which indicate the probability of failure of a given bank;
the “ZP-score” (ADZP) as in Goyeau and Tarazi (1992) and its two additive
components which we identify ADZP1 and ADZP2. ADZP1 is a measure of
bank portfolio risk whereas ADZP2 is a measure of leverage risk:
.
ADZ ¼ (100 þ average ROE)/SDROE; where ROE and SDROE are
expressed in percentage. Higher values of Z-score imply lower probability
of failure (Boyd and Graham, 1986).
.
ADZP ¼ ADZP1 þ ADZP2 ¼ (average ROA/SDROA) þ (average (total
equities/total assets)/SDROA).
Islamic banks’ assets
in total assets in 2008
Growth rate of
assets (Islamic banks)
Growth rate of
assets
a
(banking
system) Period
Saudi Arabia
b
35 33.4 19 2002-2008
Bahrain
c
29.9 37.6 7.9 2000-2008
Kuwait 29 23.2 14.3 2002-2008
UAE 13.5 59.8 38.1 2002-2008
Qatar 11.5 65.8 31.9 2002-2008
GCC average 23.8 44 22.6 2002-2008
Notes:
a
Including Islamic banks;
b
growth rate is calculated for the total of wholesale and retail while
market share is for retail only;
c
including Islamic windows
Source: International Monetary Fund (2009)
Table I.
Market share and
average annual asset
growth of Islamic and
conventional Banks
in selected countries
(percent)
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ADZP1 ¼ average ROA/SDROA.
.
ADZP2 ¼ average (total equities/total assets)/SDROA.
4.1.3 Control variables. Following prior studies, we include several bank characteristics
in the empirical analysis. Log assets is the log of total assets at the end of the year t.
Loan ratio is the loan scaled by total assets for the year t. ROE is the return on equity
ratio for the year t. For the country speci?c characteristics we will use the ratio Cont_C.
Cont_C is the ratio Islamic banks assets to total banks assets in year t in each country.
4.2 Data
We use a sample consisted of an unbalanced panel of annual report data from 2002 to
2008 for a set of Islamic banks in ?ve countries of GCC: Bahrain, Qatar, Kuwait,
Kingdom of Saudi Arabia, United Arab Emirates (Table II). We collect data for our
research from the annual reports of Islamic banks in GCC countries. Since the number
of banks has been increasing every year, we select banks existing for at least three
years (since 2005). Our ?rst sample is consisted of 45 Islamic banks in GCC countries.
We have excluded one bank because it was part of a non-Islamic bank group, hence it
is not possible to distinguish from their annual reports between the Islamic and the
non-Islamic investments or revenue. We also excluded two other banks because
the lack of information. Our ?nal sample is constituted of 42 banks observed during
the period 2002-2008. Many Islamic banks in our sample do not use the AAOIFI
presentation for their ?nancial statements. Hence, the balance sheet and the income
statement cannot help us to distinct between pro?t-loss-sharing and
nonpro?t-loss-sharing amounts. However, Islamic banks disclose such information
in the notes to the ?nancial statement.
5. Results
5.1 Descriptive statistics
Descriptive statistics of our sample are presented in Table III. The share of the income of
the Islamic ?nancing products represented, in average, 61.87 percent of the total Islamic
bank income. Both samples show suf?cient heterogeneity in different types of banking
activities. In the average, 19.07 percent of the incomes of Islamic banks come from
pro?t-loss-sharingproducts (16.45 percent for listedbanks and22.89 percent for non-listed
banks). Whereas on average 42.80 percent of the incomes of the Islamic banks come from
nonpro?t-loss-sharing products (45.10 percent for listed banks and 38.11 percent for
non-listedbanks). Listedbanks make more income fromnonpro?t-loss-sharingandhave a
higher ROE than none listed banks. However, non-listed banks earn more income from
pro?t-loss-sharing and had a higher ROA that listed banks.
5.2 Univariatemeans tests
We split our sample into different panels of banks. We compare the level of risk of
banks which are characterized by high levels of pro?t-loss-sharing activities that is
2002 2003 2004 2005 2006 2007 2008
Islamic banks 10 12 25 32 42 42 42
Table II.
Sample selection during
the period 2002-2008
Islamic banks’
income structure
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banks with a ratio of net pro?t-loss-sharing income to net operating income higher
than the third quartiles Q
50
, with banks with the same ratio not exceeding the value of
the ?rst quartile (pro?t-loss-sharing lower than Q
25
). And we undertake the similar
comparison on the basis of the dependence to the nonpro?t-loss-sharing activities
(ratio of net Non_Pro?t-Loss-Sharing income to net operating income higher than Q
50
versus Non_Pro?t-Loss-Sharing lower than Q
25
).
5.2.1 Islamic bank risk and income structure. The results in Table IV show that
on the whole for Islamic banks in GCC countries, greater reliance on
pro?t-loss-sharing income is associated with higher risk and higher insolvency risk;
whereas higher dependence on nonpro?t-loss-sharing incomes implies to lower risk
levels.
5.2.2 Income structure and Islamic banks characteristics’. For further investigations
on the characteristics of banks in the high Islamic investment category and in the low
Islamic investment category income, Table V provides the results of the test performed
on the basis of our different Islamic income category. As a whole, banks with a larger
income share of pro?t-loss-sharing investments are less reliant than loans but are also
less leveraged (higher equity ratio), and they are more pro?table (higher ROA).
However, banks with a larger income share of nonpro?t-loss-sharing investments are
more reliant than loans, have less equity ratio and are less pro?table (lower ROA
and ROE).
5.3 Multivariate regression analysis
For further investigation about this issue that is based on risk and income structure of
Islamic banks in GCC countries, we conduct in this respect cross-section OLS
TA ROA ROE EQUITY LOANS PLS NON_PLS
Sample 1: non-listed and listed banks (42 banks)
Mean 3,040,000 5.43 14.08 40.88 44.73 19.07 42.80
SD 5,790,000 3.85 7.86 27.17 27.86 20.75 28.75
Min 23,000 0.68 3.53 10.34 0.91 0.49 0.07
Max 30,700,000 16.80 41.85 99.09 93.72 83.74 95.35
Sample 2: listed banks (24 banks)
Mean 4,730,000 4.50 15.59 28.87 51.10 16.45 45.10
SD 7,130,000 3.69 8.92 17.63 28.40 16.56 28.16
Min 402,000 0.68 3.53 10.34 3.15 2.27 0.07
Max 30,700,000 16.80 41.85 73.34 93.72 62.15 94.38
Sample 3: non-listed banks (18 banks)
Mean 811,000 6.43 11.51 56.11 33.97 22.89 38.11
SD 996,000 3.92 5.77 29.66 25.55 26.10 29.34
Min 23,000 0.93 3.67 11.44 0.91 0.49 0.55
Max 3,450,000 14.57 25.75 99.09 76.23 83.74 95.35
Notes: Signi?cant at:
*
10,
* *
5 and
* * *
1 percent levels; variables de?nitions (all variables are
expressed in percentage except TA expressed in thousand US$): LOANS – loans/total assets; equity –
equity/total assets; ROA – return on assets; ROE – return on equity; TA – total assets (thousand $);
PLS – net operating income from pro?t-loss-sharing arrangement/net operating income; NON PLS –
net operating income from other Islamic products than PLS products/net operating income
Table III.
Descriptive statistics for
GCC’s Islamic banks, on
average over the period
2002-2008 (percent)
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estimations on different samples of Islamic banks. More precisely, we regress the
accounting risk measures on different categories of Islamic banks’ product and of a set
of control variables.
The estimated models are:
M_RISK
i
¼ 1þbM_ISL
i
þ
X
¥
K
M_X
ki
þ1
i
where M_RISK
i
is the mean value, for bank i, taken for the period 2002-2008, of each
accounting based risk measure computed over the period (SDROA, SDROE, ADZ,
ADZP, ADZP1, ADZP2).
M_DIV I is the mean value, for bank
I
, for the period 2002-2008, of each category of
Islamic products variable (PLS and NON_PLS).
A large set of control variables was used initially. But because of frequent
collinearity among the variables, control variables are restricted to the natural
logarithm of total assets LOG (TA), loans to total assets (LOANS), ROE and the
leverage ratio orthogonalized with total assets (EQUITY). We also include the
annual growth rate of total assets (DTA). As well as, we include the ratio Islamic banks
assets to total banks assets ratio (Cont_C) to control the country speci?c
characteristics.
Table VI shows the results obtained from regression analysis. We have separated
estimations from listed Islamic banks and non-listed Islamic banks. In all accounting
data based estimation; higher pro?t-loss-sharing activities are associated with an
increase in Islamic bank defaults risk (SDROA, SDROE, and ADZ). The coef?cient
associated to the assets growth variable MDTA is signi?cant and negative in most
of estimations with risk measures.
To cheek for robustness and to explore the effect of a relatively larger expansion into
pro?t-loss-sharing investments and non pro?t-loss-sharing investments on risk, we ran
our estimations by including dummies for diversi?cation quintiles Q
50
and Q
25
instead
Risk measures Insolvency risk measures
SDROA SDROE ADZ ADZP ADZP1 ADZP2
PLS . Q
50
Mean 0.0648 0.1183 25.542 15.264 1.458 13.806
PLS , Q
25
Mean 0.0197 0.0606 40.327 35.440 3.938 31.501
t-statistic of the mean test 2.580
* *
1.781
*
20.639 21.752
*
22.586
* *
21.471
*
NON_PLS . Q
50
Mean 0.0180 0.062 29.530 25.697 2.775 22.921
NON_PLS , Q
25
Mean 0.0399 0.099 19.104 24.957 2.988 21.969
t-statistic of the mean test 21.968
*
21.775
*
1.199 0.081 20.285 0.112
Notes: Signi?cant at:
*
10,
* *
5 and
* * *
10 percent levels for a bilateral test, respectively; t-statistics test
for the null: “risk/insolvency is not different for higher level of PLS and NON_PLS product”; variables
de?nitions: PLS – ratio of net PLS operating income to net operating income; NON_PLS – ratio of net
NON_PLS operating income to net operating income; SDROA – standard deviation of the return on
average assets; SDROE – standard deviation of the return on the average equity; ADZ – Z-score;
ADZP – “ZP-score”; ADZP1 – measure of bank portfolio risk; ADZP2 – measure of leverage risk
Table IV.
Income structure and
accounting indicators of
risk for Islamic banks in
GCC (2002-2008)
Islamic banks’
income structure
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Table V.
Income structure and
Islamic bank
characteristics for Islamic
bank in GCC countries
(2002-2008)
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Risk measures Insolvency measures
SDROA SDROE ADZ ADZP ADZP1 ADZP2
Sample 1: all banks (42)
M_NON_PLS 20.001 0.02 0.38 5.019 0.71 4.38
(t-statistics) (20.05) (20.44) (0.81) (0.35) (0.35) (0.34)
M_PLS 0.109 0.262 0.99 1.92 2.65 1.65
(t-statistics) (3.14
* * *
) (3.39
* * *
) (21.47) (0.91) (20.91) (20.91)
M_LOG(TA) 0.002 0.006 0.06 1.04 0.144 0.901
(t-statistics) (0.89) (20.90) (0.9) (0.44) (0.44) (0.44)
M_ ROE 0.046 0.423 1.09 2.06 3.02 1.76
(t-statistics) (0.63) (2.97
* *
) (20.72) (0.47) (0.49) (0.46)
MD TA 20.0002 0.0006 0.06 0.0005 0.0006 0.0005
(t-statistics) (21.41) (22.16
* *
) (0.9) (0.01) (0.00) (0.01)
M_EQUITY 0.095 0.023 1.18 3.16 4.41 2.72
(t-statistics) (3.02
* * *
) (0.31) (1.57) (1.35) (1.36) (1.35)
LOANS 0.025 0.035 0.33 0.455 0.08 0.90
(t-statistics) (0.89) (0.66) (0.62) (0.03) (0.03) (0.44)
Cont_C 0.0009 0.0007 0.003 0.03 0.004 0.025
(t-statistics) (0.65) (0.32) (21.49) (20.41) (20.41) (20.40)
R
2
46.71 40.8 26.83 18.46 18.53 18.45
Sample 2: listed banks (24)
M_NON_PLS 0.023 21.36 20.967 20.164 0.0012 20.165
(t-statistics) (1.56) (21.59) (22.61
*
) (20.60) (0.07) (0.63)
M_PLS 0.65 0.265 20.14 20.405 20.527 20.399
(t-statistics) (3.37
* * *
) (2.51
* *
) (20.27) (1.17) (22.07
*
) (21.08)
M_LOG(TA) 0.402 0.0038 0.12 20.58 20.0016 0.006
(t-statistics) (0.87) (0.39) (0.86) (21.64) (20.68) (0.2)
M_ROE 0.24 0.455 21.375 21.05 0.038 21.24
(t-statistics) (6.53
* * *
) (5.18
* * *
) (21.89
*
) (22.82
* *
) (0.79) (22.76
* *
)
MD TA 20.07 20.03 0.047 0.0034 0.0015 0.002
(t-statistics) (23.33
* * *
) (21.06) (0.84
* *
) (0.10) (0.57) (0.06)
M_EQUITY 0.11 0.917 0.892 0.122 20.017 0.21
(t-statistics) (5.12
* * *
) (0.06) (1.24) (20.47) (0.50) (0.27)
LOANS 20.002 20.195 0.203 0.104 0.0167 0.002
(t-statistics) (0.27) (0.03) (0.76) (0.53) (1.28) (0.31)
Cont_C 20.115 21.5 1.34 0.21 0.005 0.21
(t-statistics) (1.65) 23.8 (1.23) (0.27) (0.11) (0.22)
R
2
91.6 40.72 37.16 45.27 39.13 12.59
Sample 3: non-listed banks (18)
M_NON_PLS 0.26 0.342 20.814 0.85 0.47 0.802
(t-statistics) (1.10) (0.82) (0.002) (0.98) (0.51) (2.41
*
)
M_PLS 0.27 0.39 0.96 2.35 1.15 2.20
(t-statistics) (2.07
* * *
) (1.89
*
) (23.02
* * *
) (22.30) (1.41) (1.03)
M_LOG(TA) 0.030 0.054 0.016 0.115 0.64 0.109
(t-statistics) (0.55) (0.55) (0.01) (0.66) (0.34) (0.70)
M_ROE 0.63 0.001 0.61 0.06 20.42 20.006
(t-statistics) (20.07) (0.17) (0.34) (23.79
* * *
) (2.26) (3.98
* *
)
MD TA 0.0395 0.041 0.15 0.85 22.78 0.36
(t-statistics) (20.15) (0.55) (20.04) (2.81
* *
) (1.81) (22.85)
M_EQUITY 0.89 1.17 2.43 0.439 0.27 4.11
(t-statistics) (1.15) (0.86) (0.01) (1.6) (0.93) (21.68)
LOANS 0.67 0.78 4.39 20.05 0.57 27.96
(continued)
Table VI.
OLS estimations for a
sample of 42 Islamic
banks with M_PLS and
M_NON_PLS as the
independent variables
Islamic banks’
income structure
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of the values of pro?t-loss-sharingandnonpro?t-loss-sharing. Table VII shows the results
for the broad sample, for listedIslamic banks andfor non-listedIslamic banks. Overall, we
?nd that greater reliance on pro?t-loss-sharing investment is associated with higher risk
and higher default (insolvency) risk. Hence, Islamic banks which more than 50 percent of
their income comes frompro?t-loss-sharing ?nancing are faced to a higher riskthanthose
banks with less of 25 percent of the income come from pro?t-loss-sharing.
6. Discussion and conclusion
The purpose of this study is analyzing the risk implication on the ?nancial Islamic
products presented by Islamic bank in GCC countries. Our study shows that Islamic
banks expanding into pro?t-loss-sharing products present higher risk and higher
insolvency risk than banks which invest less in this kind of arrangement. As we have
listed bank prefers to invest less in nonpro?t-loss-sharing products than
pro?t-loss-sharing products. This attitude can be explained by the fact that Islamic
banks focus more on the ?nancial stability of their investments. In fact, Islamic banks as
an equity-based capital structure dominated by shareholders equity and investment
deposit holders have to offer a competitive remuneration to them especially to the
deposit holders. Indeed, in a competitiveness ?nancial market like the GCC market,
customer will be more sensitive to the volatility of returns offered on investment deposit
and may withdraw their funds in case of low remuneration. As a result, Islamic banks
have to absorb the losses, if it is the case, to make sure that the investment deposit
holders received a rate of return equivalent to the rate offered in the market. Therefore, to
manage their displaced commercial risk, Islamic banks prefer to invest more inless risky
investment (nonpro?t-loss-sharing) than pro?t-loss-sharing products to guarantee the
level of remuneration of its deposit holders. Islamic banks are strongly exposed to
massive withdrawal risk due to lower rate of return on investments deposits which
threaten the position of the bank. Depositors can at any time withdrawtheir deposit fund
to another ?nancial institution that gives higher remuneration.
Future researches have to study the relationship between the capital and the
deposits structures of Islamic banks and risks.
Risk measures Insolvency measures
SDROA SDROE ADZ ADZP ADZP1 ADZP2
(t-statistics) (0.88) (0.58) (0.03) (21.36) (1.77) (2.93)
Cont_C 1.67 2.5 5.94 0.39 10.54 13.3
(t-statistics) (21.03) (21.29) (0.06) (22.74
* *
) (2.53) (22.85)
R
2
74.26 61.95 52.36 79.83 56.94 81.31
Notes: Signi?cant at:
*
10,
* *
5 and
* * *
10 percent levels, respectively; t-statistics are corrected for
heteroskedasticity following White’s methodology; variable de?nition: M_X – mean of the variable X
for bank i over the period 2002-2008; LOG (TA) – logarithm for total assets for bank I; ROE – return
on average equity; MDTA – annual growth rate for total assets; equity ¼ equity orthogonalized with
TA; LOANS – loans/total assets; PLS – ratio of net PLS operating income to net operating income;
NON_PLS – ratio of net NON_PLS operating income/net operating income; Cont_C – ratio Islamic
banks assets to total banks assets ratio for each country; SDROA – standard deviation of the return
on average assets; SDROE – standard deviation of the return on the average equity; ADZ – Z-score;
ADZP – “ZP-score”; ADZP1 – measure of bank portfolio risk; ADZP2 – measure of leverage risk
Table VI.
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Risk measures Insolvency measures
SDROA SDROE ADZ ADZP ADZP1 ADZP2
Sample 1: all banks (42)
D_PLS Q
50
0.0095 0.013 0.018 1.605 0.22 21.37
(t-statistics) (3.13
* *
) (3.35
* * *
) (1.73
*
) (20.10) (20.10) (20.10)
D_PLS Q
25
0.011 20.033 0.512 0.736 1.01 6.35
(t-statistics) (0.61) (0.36) (1.37) (0.58) (0.58) (0.58)
D_NON_PLS Q
50
(0.041 0.122 0.31 0.409 0.55 0.323
(t-statistics) (21.28) (23.6
* * *
) (0.75) (0.28) (0.28) (0.17)
D_NON_PLS Q
25
0.045 0.132 0.3 0.372 0.49 0.349
(t-statistics) (22.15
* *
) (2.54
* *
) (0.46) (0.17) (0.16) (20.10)
M_LOG(TA) 0.0004 0.011 0.054 0.75 0.103 0.655
(t-statistics) (0.28) (21.68) (0.67) (0.28) (0.27) (0.28)
M_ROE 0.032 0.205 0.59 0.45 0.655 3.9
(t-statistics) (20.28) (1.47) (20.34) (0.78) (0.80) (0.77)
M_D TA 0.0004 0.0004 0.05 0.00047 0.006 0.00047
(t-statistics) (21.12) (21.58) (0.65) (20.04) (20.04) (20.04)
M_EQUITY 0.038 0.037 1.26 0.32 0.455 2.83
(t-statistics) (1.06) (20.65) (1.75
*
) (1.35) (1.35) (1.35)
LOANS 0.005 0.007 0.44 0.097 0.141 0.847
(t-statistics) (0.19) (0.16) (0.75) (20.05) (0.05) (20.05)
CONT_C 0.0003 0.0003 0.0049 0.044 0.006 20.038
(t-statistics) (0.28) (1.6) (21.98
*
) (20.53) (0.27) (0.053)
R
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49.31 62.84 41.72 17.04 24.85 17.06
Sample 2: listed banks (22)
D_PLS Q
50
0.0095 0.157 0.167 0.08 20.015 20.085
(t-statistics) (2.17
* *
) (3.08
* * *
) (21.88
*
) (0.73) (20.418) 0.098
D_PLS Q
25
0.006 0.0301 20.097 0.179 0.013 (20.84)
(t-statistics) (0.88) (0.73) (20.68) (1.97
*
) (1.79
*
) (1.88
*
)
D_NON_PLS Q
50
0.0015 0.084 0.212 0.149 0.010 0.139
(t-statistics) (0.16) (0.20) (0.91) (1.61) (1.32) (1.57)
D_NON_PLS Q
25
0.017 0.026 20.22 0.132 20.0102) 20.122
(t-statistics) (1.2) (0.78) (21.67) (21.57) (21.52) (21.52)
M_LOG(TA) 0.014 0.012 0.036 0.048 0.003 0.0375
(t-statistics) (1.15) (1.57) (0.66) (1.41) (1.07) (1.38)
M_ROE 0.27 0.338 22.54 21.53 0.050 21.48
(t-statistics) (6.55
* * *
) (4.6
* * *
) (22.98
* * *
) (22.84
* *
) (21.11) (22.85
* * *
)
M_D TA 20.0103 20.0002 0.014 0.0489 0.0004 0.045
(t-statistics) (21.95
*
) (23.75
* * *
) (2.56
* *
) (1.41) (0.47) (1.37)
M_EQUITY 0.078 0.234 20.49 0.742 0.033 0.708
(t-statistics) (2.79
* *
) (1.51) (0.85) (2.03
* *
) (1.1) (2.01
* *
)
LOANS 0.0009 0.062 0.176 20.008 0.0085 20.01641
(t-statistics) (0.09) (1.68) (20.80) (20.06) (0.47) (20.12)
Cont_C 0.007 2.05 0.266 0.197 0.012 0.18
(t-statistics) (20.18) (20.08) (0.31) (0.36) (0.26) (0.35)
R
2
83.52 20.01 49.62 50.06 44.38 48.76
Sample 3: non-listed banks (18)
D_PLS Q
50
0.045 0.103 0.59 0.065 0.59 0.80
(t-statistics) (3.11
* *
) (2.87
* *
) (4.09
* * *
) (4.8
* * *
) (4.09
* * *
) (4.8
* * *
)
D_PLS Q
25
0.045 0.094 0.25 0.029 0.25 0.34
(t-statistics) (0.93) (1.42) (22.11
*
) (2.48
*
) (2.11) (2.36
*
)
D_NON_PLSQ
50
0.027 0.005 0.137 0.002 0.137 0.026
(continued)
Table VII.
OLS estimations for
Islamic banks with
dummies variables on the
structure of income as the
independent variables
(cross-section estimation)
Islamic banks’
income structure
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Note
1. Moody investor service, 2009.
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2
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Notes: Signi?cant at:
*
10,
* *
5 and
* * *
10 percent levels, respectively; t-statistics are corrected for
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on average equity; TA – annual growth rate for total assets; equity – equity orthogonalized with TA;
LOANS – loans/total assets; Cont_C – ratio Islamic banks assets to total banks assets ratio for each
country; D-PLSQ
50
/D_NON_PLSQ
50
– dummy variable which takes the value of 1 when PLS/NON_
PLS for bank I is greater than the third quartile of overall sample and 0 otherwise; D-PLSQ
25
/D_NON_
PLSQ
25
– dummy variable which takes the value of 1 when PLS /NON_PLS for bank I is lower than
the ?rst quartile of overall sample and 0 otherwise; SDROA – standard deviation of the return on
average assets; SDROE – standard deviation of the return on the average equity; ADZ – Z-score;
ADZP – “ZP-score”; ADZP1 – measure of bank portfolio risk; ADZP2 – measure of leverage risk Table VII.
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Dar, H.A. and Presley, J.R. (1991), “Islamic ?nance: a Western perspective”, International Journal
of Islamic Financial Services, Vol. 1, pp. 1-9.
Stiroh, K. (2004), “Diversi?cation in banking: is non-interest income the answer”, Journal of
Money, Credit and Banking, Vol. 36, pp. 853-82.
Corresponding author
Rihab Grassa can be contacted at: [email protected]
To purchase reprints of this article please e-mail: [email protected]
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Islamic banks’
income structure
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doc_949109901.pdf