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An Exploration of the Performance between Shariah Banks and
Conventional Banks During Global Financial Turbulence1
By: M. Handry Imansyah2 and Hidayatullah Muttaqin3
ABSTRACT
It is believed that shariah banks have a higher resilience than that of conventional banks
during global financial turbulence. However, this is not quite true. The objective of this
paper is to explore the performance of shariah banks and conventional bank during the
global financial turbulence since 2008 in terms of key financial indicators such as ROA,
NPL, BOPO, CAR and others.
The method of this study is descriptive analysis of some key financial indicators. The
comparison of some key financial indicators during the global financial turbulence shows
the performance of both banks. The result of this study is mixed that there some key
financial indicators are better on shariah banks than that of conventional banks, however,
some other indicators are much better on conventional bank than that of shariah bank.
Keywords: Shariah Bank, Conventional Bank, Global Financial Turbulence
JEL: G21.
1 Paper presented at International Sustainability Forum On Islamic Economic And Business, Faculty
of Economics, Lambung Mangkurat University, 30 November 2011. 2 Faculty of Economics, Lambung Mangkurat University, Banjarmasin
3 Faculty of Economics, Lambung Mangkurat University, Banjarmasin
Introduction
The impresive growing of sharia banking in Indonesia in recent decades is
extraordinary phenomenon. However, this phenomenon causes fear of rapid growth that
can doubt the stability and performance. The study of performance of shariah banks
compared to conventional bank is relatively scarce ini Indonesia.
Loghod (2010) found in his study in The Gulf Cooperation Council Countries
(GCC), have dual banking system where shariah and conventional banks are operating side
by side, that there is no difference of the performance between these two system.
The objective of this paper is to explore the performance of shariah banking system
and conventional banking system in Indonesia. Outline of this paper is as follows, after the
introduction, a literature review, methodology and data, results and discussion and finally
conclusion.
Literature Review
Some researchers tried to assess the performance of banks during the global
financial crisis. This study could be linked to likelihood of a banking crisis because the
financial crisis. Financial crisis could be the beginning of the crisis in the banking sector if
the banking sector does not have a strong resistance from the capital side and management.
Associated with the management of banks, banking performance will be closely related to
the efficiency of the internal side and the macroeconomic situation of the external side.
Beck, Demirgüç-Kunt and Merrouche (2010) states that Shariah banks are more efficient
than of the conventional banks. In addition they also found that Shariah banks have a
larger capitalization, but the Shariah banks are not more stable than that of the
conventional banks. In addition, it was found also that Shariah banks had a ratio of
operating expenses and operating income (BOPO) lower compared with the conventional
banks. Beck, Demirgüç- Kunt and Merrouche (2010) also found that Shariah banks are
more efficient than that of the conventional banks which reflected a lower ratio operating
expenses and operating income.
Laeven and Valencia (2008) defines a banking crisis as a systemic crisis, ie the
banking and financial sector have failed in doing his duty to the third party in accordance
with the agreed contract. They distinguish between the crisis is systemic and not. The
article examines a variety of banking crises around the world since 1970 until 2008. Laeven
and Valencia (2008) identified about 124 banking crises around the world from 1970 to
2007. However, Reinhart and Rogoff (2008) further enrich the study of banking crises
around the world since the time of the Napoleonic wars in Denmark up to the current
banking crisis triggered by the subprime mortgage crisis. They identified that housing
prices (real estate) has a cycle of pattern and amount similar to the banking crisis for both
groups of developed and emerging countries. The results are certainly surprising, because
the macroeconomic data in emerging countries are relatively more fluctuating and unstable
proved to have similar patterns and similar magnitudes in general. These results, indicating
that the pattern that happens to have almost the same pattern.
Banking crises that occurred generally is the impact of financial crisis or a similar
crisis. Therefore, the theory of banking crises is closely associated with the financial crisis,
so the theory of financial crises are also often used to explain the banking crisis.
As stated by Hutchison and McDill (1999) that the theory of the banking crisis aimed at
more specific characteristics such as the transformation of banking currency and maturity
as well as asymmetric information thus making the banking industry is very vulnerable to a
crisis on the presence of shock (Jacklin and Bhattacharya, 1988; Diamond and Dybvig,
1986). Various economic institutions such as deposit insurance and the interest rate
structure which is determined by the market will affect the level of bank profits and provide
stimulus for bank managers to take the risk in providing credit. This means that in the
presence of deposit insurance can stimulate bank managers to act less carefully to the
management of the bank, because if there is something to be handled by the bank deposit
insurance.
Honohan (1997) explains that banking crises are generally closely related to
macroeconomic problems such as high loan-to-deposit ratio (LDR), high ratio of loans to
deposits overseas communities and the high rate of credit growth. Various studies show that
the banking problems are strongly associated with financial crises (Kaminsky and Reinhart,
1999) .. This happened in Indonesia in 1997, where the August 1997 financial crisis caused
the banking crisis in October 1997 with the closure of 16 banks. Furthermore, unsustainable
economic policies, weak financial structure, global financial conditions, currency exchange,
and political instability.
Macroeconomic instability such as monetary and fiscal expansion encourages credit
boom and the increase in prices of financial assets generally is one of the factors causing
the crisis or distress in the banking sector. While external factors such as drastically
changing terms of trade (terms of trade) and the world interest rate also plays an important
role in banking crises in various countries.
Weak financial structure as a result of overly rapid liberalization without offset by a
set of rules and adequate supervision to encourage the development of moral hazard. In
addition, governments often fail to rapidly identify institutional problems that delayed
repair if problems arise so until it becomes a situation that led to the crisis.
While Caprio and Klingebiel (1996) found the banking crises in developed countries is
generally due to external factors such as domestic interest rate differential with the outside,
the business cycle and foreign debt. Likewise Kibritcouglu (2004) showed that the main
cause is the explosion of credit banking crisis, economic recession and overvalution of the
domestic currency.
From various studies (eg Kaminsky and Reinhart, 1999; Demirguc-Kunt and
Detragiache, 1998b) banking crises are generally closely related to the liberalization in the
financial sector. In addition, the banking crisis is also caused by factors typically of
macroeconomic shocks is accompanied by a weak banking system itself.
Problem definition of the banking crisis itself is still subject to dispute. The definition of
Kaminsky and Reinhart (1999) regarding the banking crisis is characterized by problems
with balance sheet. They expressed early signs of crisis characterized by massive
withdrawals from the customer and bank closures. While the definition of banking crises by
Hardy and Pazarbasiglu (1998) mentioned when the banking system is experiencing one of
the following conditions:
1. The high non-performing loans (NPLs) that exceed 10% of all assets or 2% of Gross
Domestic Product (GDP).
2. Banking rescue costs exceeds 2% of GDP.
3. Banking nationalization or takeover by the government.
4. Massive withdrawals by customers (bank run).
5. Closure of the bank by the government either temporarily or permanently.
While Gonzalez-Hermosillo (1999) stated the best indicator to define a banking
crisis is the amount of bad loans. Demirguc-Kunt and Detragiache (1998) define a banking
crisis is one such non-performing loans greater than 10% of all assets in the banking
system. While Rojas-Suarez (1998) defines a banking crisis when the credit crunch is
greater than the average during the crisis is not plus 2 standard deviations.
Meanwhile, Imansyah and Kusdarjito (2008) tried to integrate the modeling of the
stability of the financial sector which includes foreign currency markets, banking and stock
market using macro indicators. The model developed using artificial neural network
approach and experimental results were quite good models in predicting the potential for
crisis or instability in these markets, it can even predict the instability of the financial sector
in 2008.
In the surveillance system, Logan (2000) divides into two parts depending on the
purpose. The first part is called a monitoring system that generally uses quantitative
information but also sometimes use a qualitative assessment of the financial condition or
risk profile of banking. While the second part is often referred to as an early warning
system that is aimed to look forward to the quantitative information to predict which banks
will fail or decline in the framework of the assessment criteria for development in the
future.
Meanwhile, Fuertes and Espinola (2006) which makes the model for the case of
Paraguay's banking crisis mentioning that the central bank's main objective is to maintain
monetary and financial stability. In the maintaining stability, the system of early warning is
one tool to whether and when the financial system is impaired so that it can be done in
anticipation of policy actions. In developing such modeling, and Espisnola Fuertes (2006)
using a parametric model or a logit regression analysis. They use the magnitude of non-
performing loans (NPL) as the dependent variable and a group of macro indicators
(macroprudential indicators) and micro indicators (microprudential indicators) as used was
enumerated by ADB (Asian Development Bank) in monitoring the financial system. Micro
indicators like return on equity (ROE), liquidity and equity as well as macro indicators such
as current-account deficit and indicators of economic activity is an important indicator that
can be a signal of impending banking crisis with a different signal lag. It seems that
economic activity or the potential for a recession or a slowdown in economic activity is a
good indicator as also shown by Quagliariello (2004). While Herrero (2005) also makes a
model for the Venezuelan banking crisis which found that the micro indicators as reflected
by low profit margins and low net inerest macro indicators are low Gross Domestic Product
growth is an important indicator in predicting banking crises.
Methodology and Data
This paper is in the form of exploration, the analysis used is descriptive. The
indicators analyzed are banking performance indicators are: ROA (return on assets), NPL
(non performing loans) or bad credit, or in terms of Shariah banking is the NPF (non-
performing financing), the growth rate of assets, deposits, and credit.
There are various ways to determine the definition of a crisis or fragility index. As
stated by Eichengreen and Arteta (2000) that the difference in determining the time when
the banking crisis will lead to a difference in the outcome. Thus, they declare quantitative
measure of the banking crisis is more difficult to determine. Therefore, there are several
ways to determine the definition of a crisis or pressure in the banking sector is by analysis
of events (events) such as the amount of interference or intervention against the
government's banking crisis is a sign of (pressure) in the banking sector and with statistical
methods. The final way is done by creating a composite index of a number of specific
indicators or a single indicator which is used as a benchmark for determining whether a
given period the banking sector in crisis or distress, or when a single indicator composite
index reaches a certain limit.
Kibritciouglu (2003) states there are advantages and disadvantages in determining
the period of crisis or distress in the banking sector for each approach, the event approaches
and statistical approaches. Details of the advantages and disadvantages of each approach
can be seen in Table 1.
Ideally the definition of non-performing loans in banking is the most precise
definition and the most widely used. However, data non-performing loans are sometimes
not available for public consumption and the long period of time.
While Hanschel and Monnin (2004) develop Keretanan index based on the data value of
banking shares in the capital market, balance sheet data and other unpublished data. While
Männasoo and Mayers (2005) using a credit level indicator and the ratio of deposits in
banks of foreign exchange reserves.
Definitions used in this paper based on statistical methods as used by Kibritciouglu
(2003) in the determination of a crisis or pressure. There are three important indicators used
to measure the fragility of the banking sector, namely: the level of foreign debt of the
banking sector, levels of credit, and deposits rates. This is because the three indicators
related to exchange rate risk, credit risk and liquidity risk. The formula of the index used
Kibritciouglu (2003) are as follows:
(1) Wh,
FLt= Foreign Debt in Banking Sector
CRt= Credit in Banking Sector
DPt=Deposit in Banking Sector
μ=average
δ=standard deviation
Determination of time of crisis or distress in the banking sector is the pressure when
the indexes are compiled in t has a value above the average plus standard deviation of the
month is considered a crisis. The data used are from SEKI (Economic and Financial
Statistics Indonesia) Bank Indonesia, Progress Report on Shariah Banking and Banking,
Statistics of Indonesia Banking and Shariah Banking Statistics, Bank Indonesia 2005-2011.
Data is accessed through the website of Bank Indonesia. Because many Shariah banking
data are not available on some particular months, the authors performed extrapolation to fill
the existing data in the previous month instead. This is to allow the holding of the analysis
and calculation. Based on available data, it can be calculated fragility index of conventional
and Shariah banking. Untul details can be seen in the following table.
IK
FL CR DP
t
t FL
FL
t CR
CR
t DP
DP
3
Table 1. Comparison Method To Determine The Episode of Bank Fragility Event Approach Statistical Approach
Advantages
Easier to be identified by looking at the extent of government intervention and
changes in regulations / policies.
Vulnerability index of banking sector can be made based on monthly data, so easy in the analysis and
dinterpreted.
Can be easily applied to a model of a country.
Can easily make the criteria for distinguishing a
systemic crisis and non-systemic based on
fluctuations in the index.
Disadvantages When exactly the crisis can only be
granted in a given year is not in months, so it is not useful to predict the crisis
months.
When government intervention is commonly used as a time of crisis, but it
does not reflect the exact time of
commencement of the crisis.
It is hard to determine whether or not a
systemic crisis, especially if only relying
on government intervention information.
Rather difficult for individual
researchers to collect information of
events, especially when it comes to the
case of many countries (panel data). Continuous monthly data is not
necessarily available and reliable.
Continuous monthly data is not necessarily
available and reliable.
Data may not be uniform when the researchers used
the case of many countries (panel data).
Vulnerability index does not necessarily reflect the
occurrence of any government intervention in the
banking sector.
Source: Kibritciouglu (2003) Table1.
Table 3. The Episode of Bank High Fragility (Crisis) in Indonesia (2005-2011).
Source: Bank Indonesia, processed.
In addition, comparison of performance between shariah bank and conventional
bank in financial indicators were analyzed by using non-parametric statistics to distinguish
whether there are significant differences between the two systems of performance
indicators. To measure of t test of comparison of two means is as follows4:
4 http://www.cliffsnotes.com/WileyCDA/CliffsReviewTopic/TwoSample
No. Shariah Bank Conventional Bank
1 February, March,
November 2005 Februarr-August 2005
3 May 2007 May, November 2007
4 May, September 2008
5 May, October,
November 2010 May, November 2010
6 May, July 2011
2
2
2
1
2
1
21
n
s
n
s
uut
ū1,2 = mean of population s1,2= standard deviation n1,2= number of observation Null hypothesis Ho: ū1-ū2=0 Alternative hypothesis Ha: ū1-ū2≠0
Shariah banking grew quite rapidly both in terms of assets and of the number of
offices during the period of six years. The number of Shariah banks are only 3 in 2005 to
10 banks in 2011. Hence, it grew three-fold. While the number of offices grew nearly four
(4)-fold from 304 to 1151 offices in the same period. While conventional banks are
relatively stagnant growth even tended to decline in the number, but the number of offices increased significantly from 8.236 to 13.379.
Table 3. Shariah Bank Network
2005 2006 2007 2008 2009 Sep 2010
Shariah Bank 3 3 3 5 6 10
Number of Office 304 349 401 581 711 1151
Business Unit (Office
Channeling) 19 20 26 27 25 23
Number of Office 154 183 196 241 287 237
Shariah Rural Bank 92 105 114 131 138 254
Number of Office 92 105 185 202 225 278
Source: Kusuma (2011).
Tabel 4. Conventional Bank Network
2005 2006 2007 2008 2009 Sep 2010
Conventional 131 130 130 124 121 122
Number of Office 8.236 9.110 9.680 10.868 12.837 13.379
Source: Bank Indonesia, processed
Conditions the ratio of loans to deposits (LDR) or so-called FDR (finance to deposit
ratio) in Shariah banking is quite fluctuated depending on economic conditions. In Figure1
and 2, the global economy in crisis would theoretically affect banking in Indonesia.
Transmission of this global crisis propagation through the financial sector and real sector.
Real sector in Indonesia will be affected through exports will slow with the global crisis.
This is especially true in developed countries are experiencing a crisis because the demand
for goods exported from Indonesia to the country is experiencing a slowdown. This
condition will affect the real sector in Indonesia and in turn will affect the financial sector
in Indonesia as well. This phenomenon will affect the transmission of credit and repayment
rates due to the economic outlook is less good in the international market.
Figure 1 showed that FDR in shariah banking also fluctuated during the global
crisis. The global crisis is characterized by increased fragility index in the shariah banking
sector. To suggest that a crisis occurs, the author makes the fragility index benchmark that
when passing the threshold of the average plus standard deviation. If the index value over
the threshold, then declared a crisis. It is only to facilitate in making the banking crisis
period due to increased fragility index, although no crisis according to the definition of a
banking crisis. Thus, it would be easier to analyze when the time pressure or fragility index
reached a high level or beyond normal limits. One of the widely used benchmark for this is
an average plus standard deviation. This means that if the value is exceeded it is considered
very strong pressure or abnormal, and said to be a crisis.
Figure 1. FDR of Shariah Bank
Figure 2. LDR of Conventional Bank
0
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is
50.00%
60.00%
70.00%
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100.00%
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120.00%
FD
R/L
DR
Crisis Episode FDR/LDR Poly. (FDR/LDR)
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50.00%
55.00%
60.00%
65.00%
70.00%
75.00%
80.00%
85.00%
LD
R
Crisis Episode LDR Poly. (LDR)
It appears in the graph (Figure 1) that after an intense pressure in which the fragility
index value exceeds normal limits, the ratio of FDR somewhat decreased with specific time
lag. This suggests that there is an influence of the global financial crisis on shariah banking.
Indeed, there is a slight differencee in the time period between the pressure of shariah
banking with conventional banking.
After a global crisis that began in mid-2007, FDR in shariah banks has decreased,
although still higher than the LDR in conventional banks. So there is the influence of the
global crisis on both banks. Meanwhile the performance of lending between the two
banking systems of distribution of funds to a third party (credit or financing) compared with
funds from a third party collected between shariah banks and conventional bank is higher in
Shariah banks than that of conventional banks and indeed statistically different (see Table
5).
Table 5. The Comparison of LDR/FDR
Time
LDR/FDR
Shariah Conventional
Jan 2005- Aug 2011 Mean 1.0097 0.6937
Stdeva 0.0622 0.0694
T value -30.5112
Crisis episode May
2007-Dec 2009) Mean 1.0198 0.7145
Stdeva 0.0502 0.0461
T value -40.2974
Source: BI, processed.
In Table 5, it is shown that LDR/FDR of shariah bank is higher than that of
conventional bank during the whole period and during the crisis episode. It is statiscally
significant of the difference. LDR/FDR of shariah bank is quite high (over 1) compared
with the conventional bank (only 0.7).
Meanwhile, the performance in generating revenue compared with assets that are
used or ROA (return on assets), the Shariah bank is lower than that of the conventional
banks and it is statistically significant (see Table 6). Most likely a small in ROA of Shariah
banks as compared to conventional banks ROA is due to economies of scale. Capital and
market share of Shariah banks is still relatively small compared with the conventional
banks. Therefore, the ROA of Shariah banks is smaller than that of conventional banks.
However, the ratio of operating expenses and operating income (BOPO) is lower of
shariah bank than that of conventional bank. This means that Shariah banks have higher
efficiency than that of conventional banks, and it is also statistically significant. Beck,
Demirgüç-Kunt and Merrouche (2010) in studies of other banks around the world also
found the same thing that is BOPO Shariah bank BOPO lower compared with the
conventional banks. This means that Shariah banks more efficient than conventional banks.
On the other hand, Parashar and Venkatesh (2010) found in his research that the
cost to income ratio of Shariah banks are relatively similar compared to the cost to income
ratio of conventional banks. Their study covered Middle East countries, on the other hand,
Beck, Demirgüç-Kunt and Merrouche study covered many countries around the world.
Meanwhile, Hasan and Bashir ( no year) found that ROA on conventional bank was lower
than that of shariah bank.
Table 6. The Comparison of ROA and BOPO
Time ROA BOPO
Shariah Conventional Shariah Conventional
2005-2011 Mean 1.6964 2.7599 77.3345 88.3645
Stdeva 0.3062 0.3486 5.3344 5.8354
T value 20.6293 12.5560
Crisis episode
(May 2007-
Dec 2009)
Mean 1.8644 2.7209 75.0346 86.5869
Stdeva 0.3056 0.1548 4.6541 3.8068
T value 22.5027 17.2918
Source: Bank Indonesia, processed.
Figure 3. The Return on Asset (ROA) of Shariah Bank
Figure 4. The Return on Asset (ROA) of Conventional Bank
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RO
A
Crisis Episode ROA Poly. (ROA)
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RO
A
Crisis Episode ROA Poly. (ROA)
Figure 5. The Ratio of Operational Cost and Income of Shariah Bank
Figure 6. The Ratio of Operational Cost and Income of Conventional Bank
In terms of NPL, the performance of shariah banks is better than that of
conventional banks and it is also statistically significant. However, during crisis period, the
performance of shariah bank is worse than that of conventional bank. This suggests that
shariah bank has more exposed to global crisis than that of conventional bank.
Capital adequacy ratio (CAR) of shariah bank is lower than that conventional bank.
Indeed, during the global crisis, CAR of shariah bank declined, but CAR of conventional
bank increased. This phenomenon showed that shariah bank experienced capital problems
during global crisis. However, overall, the CAR of shariah bank has an uptrend.
Meanwahile, the CAR of conventional bank has a downward trend.
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BO
PO
Crisis Episode BOPO Poly. (BOPO)
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Crisis Episode BOPO Poly. (BOPO)
Figure 7. The CAR of Shariah Bank
Figure 8. The CAR of Conventional Bank
Table 7. Comparison of NPL/NPF and CAR
Source: Bank Indonesia, processed.
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Crisis Episode CAR Poly. (CAR)
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CA
R
Crisis Episode CAR Poly. (CAR)
Time NPL/NPF CAR
Shariah Conventional Shariah Conventional
2005-2011 Mean 0.0449 0.0544 13.5555 17.8941
Stdeva 0.0089 0.0204 2.4745 1.1392
T value 3.8128 14.3339
Crisis episode
(May 2007-
Dec 2009)
Mean 0.0500 0.0464 12.3092 18.6716
Stdeva 0.0085 0.0083 1.3055 1.6803
T value -2.6870 26.9107
Figure 9. The performance of NPF of Shariah Bank
Figure 10. The performance of NPL of Conventional Bank
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08
M1
0
M3
20
09
M8
20
09
M1
20
10
M6
20
10
M1
1
M4
20
11
2.00%
2.50%
3.00%
3.50%
4.00%
4.50%
5.00%
5.50%
6.00%
6.50%
7.00%
NP
L/N
PF
Crisis Episode NPL/NPF Poly. (NPL/NPF)
0
0.2
0.4
0.6
0.8
1
1.2
M1
20
05
M6
20
05
M1
1
M4
20
06
M9
20
06
M2
20
07
M7
20
07
M1
2
M5
20
08
M1
0
M3
20
09
M8
20
09
M1
20
10
M6
20
10
M1
1
M4
20
11
Cris
is
2.00%
3.00%
4.00%
5.00%
6.00%
7.00%
8.00%
9.00%
10.00%
NP
L
Crisis Episode NPL Poly. (NPL)
Conclusion
Shariah bank increased significantly in number of bank and offices, on the other
hand, conventional bank declined in number but increased in number of offices.
LDR/FDR of shariah bank is very high and even higher during the crisis.
Meanwhile LDR of conventional bank is relatively low but keep increasing during
the crisis.
ROA of shariah bank is lower than that of conventional bank. However, during the
crisis, ROA of shariah bank is higher than that of conventional bank.
BOPO or ratio of operational cost and income of shariah bank is lower than that of
conventional bank. This lower ratio reflects a higher efficiency, even during the
crisis episode. This showed that shariah bank has a more efficient than that of
conventional bank during the crisis period.
Capital adequacy ratio (CAR) of shariah bank is lower than that conventional bank.
Indeed, during the global crisis, CAR of shariah bank declined, but CAR of
conventional bank increased. However, overall, the CAR of shariah bank has an
uptrend. Meanwahile, the CAR of conventional bank has a downward trend.
The performance of NPL for shariah banks is better than that of conventional banks
and it is also statistically significant. However, during crisis period, the performance
of shariah bank is worse than that of conventional bank.
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Appendix Table 1. The Performance of Some Indicators of Shariah Bank
Appendix Table 2. The Performance of Some Indicators of Conventional Bank
-1.50
-1.00
-0.50
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
M12
200
5
M5
2006
M10
200
6
M3
2007
M8
2007
M1
2008
M6
2008
M11
200
8
M4
2009
M9
2009
M2
2010
M7
2010
M12
201
0
M5
2011
Fra
gil
ity I
ndex
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
Ass
et G
wro
wth
Shar
iah
Fragility Index Asset Growth Shariah
-1.00
-0.50
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
4.00
M1 2
006
M7 2
006
M1 2
007
M7 2
007
M1 2
008
M7 2
008
M1 2
009
M7 2
009
M1 2
010
M7 2
010
M1 2
011
M7 2
011
Fra
gil
ity
In
dex
-40.00%
-20.00%
0.00%
20.00%
40.00%
60.00%
80.00%
100.00%
120.00%
140.00%
160.00%
Cap
ital
Gro
wth
Sh
aria
h
Fragility Index Capital Growth Shariah
-1.00
-0.50
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
4.00
M12
2005
M6 2
006
M12
2006
M6 2
007
M12
2007
M6 2
008
M12
2008
M6 2
009
M12
2009
M6 2
010
M12
2010
M6 2
011
Fra
gil
ity I
ndex
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
Fin
anci
ng G
row
th
Fragility Index Financing Growth Shariah
-1.50
-1.00
-0.50
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
M12
2005
M6 2
006
M12
2006
M6 2
007
M12
2007
M6 2
008
M12
2008
M6 2
009
M12
2009
M6 2
010
M12
2010
M6 2
011
Fra
gil
ity
In
dex
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
Th
ird
Par
ty F
un
d S
har
iah
Fragility Index Third Party Fund Growth Shariah
-1.50
-1.00
-0.50
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
M1
2006
M6
2006
M11
200
6
M4
2007
M9
2007
M2
2008
M7
2008
M12
200
8
M5
2009
M10
200
9
M3
2010
M8
2010
M1
2011
M6
2011
Fra
gil
ity I
ndex
0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
Per
tum
buhan
DP
K
Fragility Index Third Party Fund Growth
-1.50
-1.00
-0.50
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
M1 200
6
M6 200
6
M11
2006
M4 200
7
M9 200
7
M2 200
8
M7 200
8
M12
2008
M5 200
9
M10
2009
M3 201
0
M8 201
0
M1 201
1
M6 201
1
Fra
gil
ity
In
dex
0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
Ass
et
Gro
wth
of
Co
nv
en
tio
na
l
Fragility Index Asset Growth of Conventional
-1.50
-1.00
-0.50
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
M1
2006
M6
2006
M11
200
6
M4
2007
M9
2007
M2
2008
M7
2008
M12
200
8
M5
2009
M10
200
9
M3
2010
M8
2010
M1
2011
M6
2011
Fra
gil
ity
In
dex
0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
30.00%
35.00%
40.00%
Cap
ital
Gro
wth
Fragility Index Capital Growth
-1.50
-1.00
-0.50
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
M1
2006
M6
2006
M11
200
6
M4
2007
M9
2007
M2
2008
M7
2008
M12
200
8
M5
2009
M10
200
9
M3
2010
M8
2010
M1
2011
M6
2011
Fra
gil
ity
In
dex
0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
30.00%
35.00%
40.00%
45.00%
Cre
dit
Go
wth
Fragility Index Credit Growth