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

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Crisis Episode FDR/LDR Poly. (FDR/LDR)

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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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A

Crisis Episode ROA Poly. (ROA)

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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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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)

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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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