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1. Simulation Based Stress Testing on The 1-16

Indonesian Islamic Banks Rifki Ismal

2. Impact of Global Financial Crisis on Islamic and Conventional Stocks 17-29 in Emerging Market: An Application of ARCH and GARCH Methods Raditya Sukmana & Muhammad Kholid

3. Ranking of Islamic Banking Efficiency Based on Decision Tree in Iran. 30-43 Mahdi Salehi

4. Islamic Finance For Small and Medium-Sized Enterprises 44-54 Abdulaziz M. Abdulsaleh

5. The Conversion Effects of Islamic Unit to Full Fledged System Islamic 55-63 Banks in Indonesia Dodik Siswantoro

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!BANKING INDICATORS 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012*

Islamic banks (unit) 2 2 2 2 3 3 3 3 5 6 11 11 11Islamic banking units (unit) 3 3 6 8 15 19 20 25 27 25 23 23 23Islamic rural banks (unit) 79 81 83 84 88 92 105 114 131 138 150 151 155Total offices (unit) 146 182 229 337 443 550 567 683 951 1223 1763 1796 2000Total asset (trillion Rp) 1.79 2.72 4.05 7.86 15.33 20.88 26.72 36.53 49.55 66.01 97.51 95.74 149.3Total financing (trillion Rp) 1.27 2.05 3.28 5.53 11.49 15.23 19.53 27.94 38.19 46.88 68.18 69.72 103.7Total deposit (trillion Rp) 1.03 1.81 2.92 5.72 11.86 15.58 20.67 25.65 36.85 52.27 76.03 75.81 114.61*Source : Bank Indonesia, data up to February 2012 *

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Simulation Base on Stress Testing on the Indonesian Islamic Bank

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AJIBF| Vol. 1. No.2| Dec 2012

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Stock market crash around the world during the crisis period demonstrated the financial contagion of recent global financial crisis. Not with standing the financial crisis firstly hit the stock markets in the United States and other developed market, it is soon spread around the world to hit stock markets in emerging country like Indonesia and other Southeast Asia countries. This is due to the rapid transmission of information across market which lead to the spreading of financial crisis from one country to another, even when underlying economic fundamentals are different (Ahlgren & Antell, 2009). Hence, high economic linked between emerging market and developed market just becomes the conductor of the contagion. With such markets environment, investors need a guide to make effective investment portfolio, an investment that can stand market shocks and least risky. Risk is important in investment since


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risk is a factor that shapes individuals’ decision to make investment (Lipe, 1998; Yang and Qiu, 2005). Knowing the investment risk, it will guide investor in developing effective investment portfolio especially during the crisis period.

In view of rapid development of Islamic finance, and thus Islamic investment, this paper tries to measure and compare the resilience of Islamic stock index and conventional stock index during the financial crisis. This study will further be used as new guide for investors in emerging stock markets to create effective investment portfolio. The study examines the risk performance of stock markets in Indonesia. The stock market has two indices namely, Jakarta Islamic Index (JAKISL) and its conventional counterpart, Jakarta Composite Index (JCI). (JAKISL) is a subset of (JCI) where all stocks of (JAKISL) are part of (JCI).

(JAKISL) consists of sharia compliant stocks that have gone through sharia screening process. The screening process measures sharia compliant of stock using three approach of valuation namely, production or activity method, income method and capital structure method (Rosly, 2005). The components of the (JAKISL) are 30 listed companies, approved by the Sharia Supervisory Board of Danareksa Investment Management to be in line with Sharia rules. The index is calculated with a base value of 100, with January 1, 1995 as the base year. The trading of the index was started on July 3, 2000 (Rahim, Ahmad N & Ahmad I, 2009).

Risk performance of (JAKISL) and (JCI) is measured using (ARCH) and (GARCH) methodologies. These methodologies are useful to measure volatility of individual stocks or index. The volatility of index is measured throughout the period prior, during and after 2008’s financial crisis. This is to find out whether financial crisis affects to the volatility of stocks and severity of the effect towards Islamic and non-Islamic/conventional index.

Particularly, The point that we try to hihglight in this regards is comparison between risk performance of shariah and conventional stock indices. Recall that stock price is found to provide vital information about the future economic activities. An unexpected increase in the stock price suggests that future dividend growth is higher. Given that the dividend is an important component of gross domestic product (GDP), and is also likely to be positively correlated with the other components of (GDP), the stock price increase may merely reflect higher expected future output. (Guo, 2002).

Stock market in Indonesia also reflects the expected future of Indonesian economy. As an emerging country, Indonesia might be influenced by what has been happening in the global world. For example in Asian crisis 1997-1998, Indonesian stock market plunged to the worst ever, and it indicated the downturn of the Indonesian economy.

By including recent global financial crisis period in our observation period it enables us to measure risk performance of both indices during normal and crisis time. Measuring risk performance in boths condition is expected to reveal the comprehensive risk behaviour of the both indices. In respect to this objective, this observation actually can be done during any crisis happend in Indonesia, for instance Southeast Asia financial crisis in 1998. However, we shall consider availability stock market data to choose which crisis period to work on. As we might expect, there was no sufficient stock market data in Indonesia in 1998 to work on (particularly on

Impact of Global Financial Crisis on Islamic and Conventional Stock in Emerging Market"

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the Islamic stock index). Apperently, the recent global financial crisis in 2008 which also affected stock market in Indonesia happen to provide suitable observation environment where stock market data is available and crisis period can be identified. Finding of this research is useful to guide investor in their investment decision.

This paper subdivides into five sections to cover the above discussion; first section is introduction to the research that includes background and objectives of the study. The next section discusses Islamic stock index and sharia screening process to provide understanding and give appreciation about Islamic stock and the process to determine Islamic stocks. Observation data and methods are discussed in section 3 while the empirical result and analysis will be described and discussed in section 4. Following it, the discussion ends with conclusion.

ISLAMIC STOCK INDEX AND SHARIA SCREENING PROCESS

It is important to know about Islamic stock index and the process to determine sharia compliance stocks that form the index. The relevance to know these is lied on the purpose of this paper which is to measure the resilience of the Islamic stock index compare to its conventional counterpart. This paper is expected to provide a guide for investor in their investment decision especially during financial crisis. Hence, a clear understanding about Islamic stock index and sharia screening process is required.

The fundamental different between Islamic index and conventional index is that the former requires stocks to be sharia compliant while the latter has no such requirement. A sharia compliant stock, in simple term, can be described as stock of company whose activities are free from riba (interest), gharar (uncertainty), maysir (gambling) elements and prohibited activities like producing products or delivering services which against Islamic teaching like pornography, producing/selling alcohol, casino etc.

Sharia stock index consist of stocks that are available in stock markets and have been selected under stock screening process to determine whether a stock is sharia compliant stock (permissible/halal stock) or otherwise. According to (Rosly 2005), there are three approaches in stock screening process. Those approaches are activity or production method, income method, and capital structure method. For the production method or activity method, a stock is declared permissible (halal) when the issuing company produces output or products that are free from the prohibitive elements of riba, gambling, intoxicants, pork and pornography. Then under income method, income derived from reserves and investments securities must be free from interest/ Riba. The Dow Jones Islamic Index is the most conservative in this regards. Companies that hold cash and interest-bearing securities exceeding 33 percent of total assets are excluded from the index. The third method is capital structure method where debt to equity ratio of the issuing company becomes the key to measures stock compliance. The bigger the ratio, the more dependent is the bank on debt financing with payments and receipts of interest fully implicated. Nevertheless, today the full compliance is impossible. On the leverage factor, a debt to equity


#6""

ratio of less than (45%) will claim Islamic legitimacy while Dow Jones Islamic Index at less than (33%).

To the best of the author knowledge, study on the comparison of the risk between Islamic and conventional stock is only done by (Zoubi and Maghyereh 2007). It uses the sophisticated method of Value at Risk (VaR) methodologies’ such as Risk Metrics, Student-t APARCH and skewed Student-t APARCH covering from year 1996 to 2005. In conclusion, the result suggests that the value of VaR is greater for (DJIM) than for (DJIS) Islamic. This means that Islamic index has a risk which is significantly less than the board market basket of stocks. This present study aims to extend the study done by Zoubi and Maghyereh (2007) using the emerging market case of Indonesia where Islamic and conventional stocks exists.

DATA AND METHODOLOGY

Data

The data used in this study consists of daily series (last price) on Jakarta Composite Index (JCI) and Jakarta Islamic Index (JAKISL) from January 3, 2001 to 30 December 2009 (2185 observations). Briefly, JCI reflects an index of an Indonesian stock market and JAKISL refer to the selected Indonesian stocks which have been filtered with the shariah values/parameters. All the data are retrieved from Bloomberg. Since the focus of this study is to examine the impact of crisis, hence dummy variable will be adopted. The decision to create dummy variable which represents the crisis period will be subjective and this paper set the crisis starts at March 2008. The reason for this is that Bear Stern was provided loan by Federal Reserve to avert collapse of the company. When such big company requested a help from US government, it was a sign that the crisis start as this influenced the market confidences and triggered market panic that in shortly spread around the globe. Furthermore, with regard to the last day of crisis, this study argues that crisis ended at July 31, 2009. This date was selected based on the fact that Bank Indonesia rate, as an important instrument in conducting the Indonesian monetary policy, has been stable (Indonesian Economic Report 2009). Hence it is argued that particular date was a signal that crisis ends.

Volatility Measures

The volatility approach used is based on an Autoregressive Conditional Heteroscedasticity model (ARCH) which is introduced by Engle (1982). Furthermore, other method of Generalized Autoregressive Conditional Heteroscedasticity (GARCH) by Bollerslev (1986) will also be examined. These models are adopted since it allows for heteroscedasticity in the residual series. Furthermore, these models take into account the volatility shock to persist over time (Ibrahim, 2002). (GARCH) p.q model is as follows:


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p

i

q

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ttt

t

r

itit

heh

hNIe

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1 11

210

1

11

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Model 1 above represent the conditional mean equation which is modeled as an autoregressive process. The r is selected such that the residuals (et) are not serially correlated. Model 3 refers to the conditional variance equation. The ht, conditional variance depends on lagged squared errors and lagged conditional variances. In order to be well defined (GARCH) model, it necessitates that coefficient of the lagged squared errors and lagged conditional variances are non-negative and their sum is less than unity (Ibrahim, 2002).

To start with, we will depict the descriptive statistics of all the variables such as mean, median kurtosis etc. following it, we will ensure that the non homoscedastic or heteroscedasticity in the residual present in the model by testing it with the (ARCH LM) Test. Having known that the result is as expected, we proceed to test the main objective of this paper that is whether crisis as represented by dummy variables extend its influence to the (JCI) and (JAKISL).

EMPIRICAL RESULT AND ANALYSIS

Descriptive statistics of the all variables are given in table 1. From the table, some observations are made. First, total number of observation used in this paper during the period of study is 2185. Second, for the mean, median, maximum and minimum, (JAKISL) is relatively low as compare to that of (JCI). For instance, (JAKISL)’ mean of 203.8 is much smaller comparing to (JCI’s) mean of 1211.4. Median also provides similar result that the value for (JAKISL), which is 178.53, is much lower compare to the median for JCI which is 1085.7. Third, on the skewness of the variables, (JAKISL) and JCI exhibit the value of 0.61 and 0.54 respectively. This positive skewness indicates that the distribution has a long right tail. With regard to the peakedness or flatness of the distribution of the series as represented by the kurtosis, both variables reveal that all distribution is platykurtic (flat) since those two value of the kurtosis are less than 3. A detail description can be seen in table 1 below.

Tabel 1: Descriptive Statistics

JAKISL JCI

Mean 203.8156 1211.449

Median 178.5340 1085.744


##""

-.20

-.15

-.10

-.05

.00

.05

.10

2001 2002 2003 2004 2005 2006 2007 2008 2009

RJAKISL

maximum 517.8140 2830.263

Minimum 48.99100 337.4750

Std. Dev. 129.7691 735.0121

Skewness 0.616586 0.546737

Kurtosis 2.206686 1.993350

Jarque-Bera 195.7453 201.1139

Probability 0.000000 0.000000

Sum 445337.0 2647016.

Sum Sq. Dev. 36778589 1.18E+09

Observations 2185 2185

Having known on the descriptive statistics of those two variables, we proceed to clarify whether

heteroscedasticity is presented in the residual. However, before clarifying the possibility of the

existence of the heteroscedasticity, it is worth to look into the graphical distribution on the return

of (JCI) as well as (JAKISL) as shown in the graph 1 and graph 2.

Graph 1: Graphical Distribution of the Return of Jakarta Islamic Index (JAKISL)


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-.12

-.08

-.04

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.04

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2001 2002 2003 2004 2005 2006 2007 2008 2009

RJCI

Graph 2: Graphical Distribution of the Return of Jakarta Composite Index (JII)

From the above figures, it shows that there exists periods with larger and smaller volatility in both samples. For example, during mid 2008 to mid 2009, it is seen that volatility is relatively high compared to other periods (such as during 2003 or during mid 2004 to mid 2005). This suggests that the crisis, which is occurred in that period (mid 2008 to mid 2009) may affect the performance of both stock indices. Furthermore, still in the same period, volatility return on the Islamic index seems to be slightly lower than that of the JCI. However, in order to decide whether heteroscedasticity is truly exist, we need to adopt the statistical measurements of Breusch-Pagan (ARCH) test or (ARCH LM) test. Results of the tests for both of variables are shown in the Table 2 and 3.

Table 2: A Simple AR (1) Model and Testing for ARCH(1) effects for JAKISL

Variable Coefficient Std. Error t-Statistic Prob. C 0.223711 0.181026 1.235793 0.2167JAKISL(-1) 0.999712 0.00075 1333.654 0.0000R-squared 0.998775Durbin-Watson stat 1.847425

ARCH Test:F-statistic 216.5407 Prob. F(1,2181) 0.0000Obs*R-squared 197.1638 Prob. Chi-Square(1) 0.0000

Dependent Variable: RESID^2Variable Coefficient Std. Error t-Statistic Prob. C 341.4874 42.00866 8.128978 0.0000RESID^2(-1) 0.371283 0.019882 18.67435 0.0000R-squared 0.137853Durbin-Watson stat 2.190877

From table 2 and 3, the important part to confirm the existence of heteroscedasticity is on the (ARCH) test. The Obs*R-Squared statistics are 197.1 (p value = 0.00) and 300.9 (p value = 0.00) for (JAKISL) and (JCI) respectively. This clearly suggests that null hypothesis of non


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heteroscedasticity or homoscedasticity is rejected even in (1%). On other words, (ARCH) (1) effect are present. To check the robustness of the result, this study also employs high order ARCH effects (order 6 will be used). Results are shown in table 4 and 5 below.

Table 3: A Simple AR(1) Model and Testing for ARCH(1) effects for JCI

Variable Coefficient Std. Error t-Statistic Prob. C 1.012176 0.96176 1.05242 0.2927JCI(-1) 0.999967 0.000679 1472.45 0.0000R-squared 0.998995Durbin-Watson stat 1.794275

ARCH Test:F-statistic 348.7314 Prob. F(1,2181) 0.0000Obs*R-squared 300.9334 Prob. Chi-Square(1) 0.0000

Dependent Variable: RESID^2Variable Coefficient Std. Error t-Statistic Prob. C 341.4874 42.00866 8.12898 0.0000RESID^2(-1) 0.371283 0.019882 18.6744 0.0000R-squared 0.137853Durbin-Watson stat 2.190877

Table 4: Testing for ARCH(6) effects for JAKISL

ARCH Test:F-statistic 73.42189 Prob. F(6,2171) 0.0000Obs*R-squared 367.4003 Prob. Chi-Square( 0.0000

Dependent Variable: RESID^2Variable Coefficient Std. Error t-Statistic Prob. C 8.400199 1.54278 5.44487 0.0000RESID^2(-1) 0.189717 0.02146 8.84256 0.0000RESID^2(-2) 0.194303 0.02179 8.91641 0.0000RESID^2(-3) 0.045181 0.02202 2.05188 0.0403RESID^2(-4) 0.125731 0.02203 5.70816 0.0000RESID^2(-5) 0.067303 0.02179 3.08875 0.0020RESID^2(-6) -0.028641 0.02156 -1.32848 0.1842R-squared 0.168687Durbin-Watson stat 1.99488


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Table 5: Testing for ARCH(6) effects for JCI

ARCH Test:F-statistic 99.6077 Prob. F(6,2171) 0.0000Obs*R-squared 470.148 Prob. Chi-Square( 0.0000

Dependent Variable: RESID^2Variable CoefficienStd. Error t-Statistic Prob. C 213.943 41.9555 5.09927 0.0000RESID^2(-1) 0.26062 0.02141 12.1722 0.0000RESID^2(-2) 0.2259 0.02204 10.2514 0.0000RESID^2(-3) -0.02134 0.02242 -0.95172 0.3413RESID^2(-4) 0.11629 0.02243 5.18494 0.0000RESID^2(-5) 0.09514 0.02204 4.31728 0.0000RESID^2(-6) -0.06977 0.02146 -3.25087 0.0012R-squared 0.21586Durbin-Watson stat 1.98996

Result of Table 4 and 5 strengthen our previous argument that ARCH effect exist. The Obs *R-Squared statistics are 367.4 and 470.1 for both (JAKISL) and (JCI). These results are even higher than that with the lag of 1. It suggests a massive rejection of the null hypothesis. Moreover, almost all of the lagged squared residuals are all highly statistically significant with the exception of lag 6 in (JAKISL) and lag 3 in (JCI). It is then clear for this equation specification that an ARCH model will provide better results. Next is to check whether volatility on both indices is affected by the crisis.

Table 6: An ARCH-GARCH (1,1) Model for the JAKISL

Dependent Variable: JAKISLMethod: ML - ARCHConvergence achieved after 25 iterations

Coefficient Std. Error z-Statistic Prob. C 0.017473 0.07756 0.2253 0.8217

JAKISL(-1) 1.001244 0.00057 1752.85 0.0000DUMMY -0.186264 0.40495 -0.45996 0.6455

C 0.036192 0.00763 4.74237 0.0000RESID(-1)^2 0.093338 0.00797 11.7122 0.0000GARCH(-1) 0.908639 0.00733 123.951 0.0000

DUMMY 0.409453 0.21386 1.9146 0.0555R-squared 0.998774Durbin-Watson stat 1.849226

Mean Equation

Variance Equation


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Table 7: An ARCH-GARCH (1,1) model for the VD-!

Dependent Variable: JCIMethod: ML - ARCHConvergence achieved after 33 iterations

Coefficient Std. Error z-Statistic Prob. C -0.142968 0.39346 -0.36336 0.7163

JCI(-1) 1.0016 0.00049 2054.948 0.0000DUMMY -2.392962 2.0953 -1.14206 0.2534

C 1.128338 0.21598 5.224228 0.0000RESID(-1)^2 0.122462 0.00926 13.22244 0.0000GARCH(-1) 0.881413 0.00822 107.1821 0.0000

DUMMY 16.95182 6.69926 2.530403 0.0114R-squared 0.998995Durbin-Watson stat 1.79708

Mean Equation

Variance Equation

Table 6 and 7 reveal some important results that will be used in identifying whether crisis affects both stock indices. This study examines our estimation of the generalized mode to the case where both p and q1 are set to 1 since several studies indicate the adequacy of this specification in fitting time series (Ibrahim, 2002).

From the variance equation in both tables, it suggests that crisis affects the variance of both indices. The probability of the dummy in the (JAKISL) which is 0.055 is significant in the (10%). Meanwhile, crisis has shown to have more significant (5%) in the context of (JCI) with the probability of 0.0114. In terms of the magnitude as represented by the coefficient, it shows that the coefficient of the crisis to the volatility of (JAKISL) is 0.40 whilst that for JCI is 16.952.

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With respect to the mean equation, it reveals that the existence of crisis is not significant in influencing both indices. This is shown by the probability of 0.645 and 0.25 for (JAKISL) and (JCI).

Comparing the result of variance equation (in terms of the significances and the magnitude) in both models, it suggests that the crisis which starts to occur in mid 2008, affects the volatility in both indices namely (JAKISL) and (JCI). Volatility also measures the risk. Therefore, the existence of the crisis will provide more risk to the (JCI) as this index is more volatile. In contrary, although crisis also creates volatility for (JAKISL), but the degree is much less than that of the (JCI). In other word, crisis provides less risk for the (JAKISL).

With this result, it suggests that investing in the stocks in the (JAKISL) will be facing less risk as compare to that of the stocks in (JCI). Hence, (JAKISL) is another better alternative for the investor especially during crisis time.

Table 6 & 7 have provided us the guidelines for the investors especially during crisis. There are two types of investors based on the risk appetite namely risk seeker and risk avoider. The former refer to the investors who like to opt for high risk which is normally followed by high return. The latter refers to the investors who try to avoid such a high risk. Certainly, for the investors who are risk seeker, (JCI) may be suited for them as (JCI) prove to have high risk. Conversely, investors who are risk avoider may opt for collections of stock in (JAKISL) due to its less volatility.

There are at least two policy recommendations derived from this study: firstly, the result facilitates investor with the risk profile on each index. This certainly brings a more accurate analysis as to kinds of investment venture that suit with investors’ risk appetites. Secondly, the result suggests that the shariah screening process is important not only it eliminates the non shariah stocks but also it provides less risk kind of investment which is inline with the nature of Islamic value of small uncertainty (gharar shaghir).

The further study that needs to be done is to look into the case of other countries which allow Islamic and conventional stock coexists in their capital market. This is important to see the consistency of the result with this study and the previous study Zoubi and Maghyereh (2007). If

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On (EGARCH), the p value of dummy crisis in the Islamic stock market shows not significant while that is not the case of (JCI). P-value for (JCI) is 0.0043 which means it is significant in 1 percent level. It implies that crisis does influence the conventional index and not the Islamic index. The same hold true in the case of (TARCH)H*


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the same results are obtained than we can conclude that majority of the Islamic stock are having lesser risks. This will give some important information to the investors since they can have a portfolio of Islamic stocks, which have proven to have lesser risk, in several countries.

5. CONCLUSION

Financial crisis could affect the volatility of both Islamic stock index and conventional stock index. An empirical study on two stock indices of Jakarta Islamic Stock Index (JAKISL) and Jakarta Composite Index (JCI) is conducted to measure the magnitude of effect of the financial crisis towards the indices volatility. Even though volatility of both indices is affected by financial crisis, the study reveals that the magnitude of volatility of the indices is different where volatility of (JCI) is greater than that of (JAKISL). This finding shows that Islamic stock index is more resilience towards crisis compare to conventional stock index. As volatility measure risk, hence (JAKISL) is less risky than (JCI) especially during crisis time. This finding can guide investors in their investment decision by providing information on the risk exposure on those two indices. For the risk seeker investor, stock collection in (JCI) is suited to them. Meanwhile for the risk avoider investors which always seek a lower risk, they will opt for (JAKISL) which prove to have a lesser risk. For the muslim investor who are valued with the Islamic norm of the allowing small uncertainty (gharar shagir), they will definitely select stocks from (JAKISL).

REFERENCES

Bollerslev, T. (1986),” Generalised Autoregressive Conditional Heteroscedasticity”, Journal of Economic Surveys,7,pp. 305-62

Engle, R.F. (1982),” Autoregressive Conditional Heteroscedasticity with estimates of the Variance of U.K. Inflation”, Econometrica, 50,pp 987-1008

Guo, H (2002),” Why Are Stock Market Returns Correlated with Future Economic Activities? REVIEW, The Federal Reserve Bank of St.Louis March/April.

Ibrahim, M (2002),” Volatility Interactions Between Stock Returns and Macroeconomic Variables: Malaysian Evidence,” Savings and Development no 2-2002-XXVI

Lipe, M. G. (1998), “Individual investors' risk judgments and investment decisions: the impact of accounting and market data,” Accounting, Organizations and Society 23, 625-640.

Yang, J. and Qiu, W. (2005), “A measure of risk and a decision-making model based on expected utility and entropy,” European Journal of Operational Research 164, 792-799.

Rosly, S.A. (2005), “Critical Issues on Islamic Banking and Financial Markets”, Dinamas Publishing, Kuala Lumpur.


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Ahlgren, N & Antell, J. (2009),”Stock Market Linkages and Financial Contagion: A Cobreaking Analysis,” The Quarterly Review of Economics and Finance 50 (2010) 157 – 166.

Rahim, F.A., Ahmad, N., Ahmad, I, (2009),”Information Transmission between Islamic Stocks Indices in South East Asia,” International Journal of Islamic and Middle Eastern Finance and Management, Vol. 2 No. 1, 2009 pp. 7-19

Zoubi, H.A., & Maghyereh, A.I. (2007),” The relative Risk Performance of Islamic Finance: A new Guide to Less Risky Investments.” International Journal of Theorethical and Applied Finance. Vol.10, No.2 pg 235-249.


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RANKING OF ISLAMIC BANKING EFFICIENCY BASED ON DECISION TREE IN IRAN

Mahdi Salehi

ABSTRACT

Purpose – In this study, it is attempted to examine the Islamic banking practice in Iran based on new scientific methods.

Design/methodology/approach- It is used in financial ratios to demonstrate the efficiency or non-efficiens of banks to assess the financial health of listed banks in Tehran Stock Exchange. The assessment of these ratios with use of decision tree as a non-parametric method for modeling is recommended to presenting this model. Information about the financial health of banks could be effective on the decisions of different groups of banks’ financial reports users, including shareholders, auditors, stock exchange, central bank and etc.

Findings – the results of the study show that Decision Tree is a strong approach in attemping to classifying Islamic banks in Iran.

Originality/value- So far, several studies have been conducted in various countries on the topic of this study. Considering the importance of Islamic banking, it is almost the first study in Iran and the outcomes of this study may be helpful to Iranian economy.

Key words: Islamic Banking, efficiency, Shariah, Iran

INTRODUCTION

One of the most important institutions in today’s society is bank. Today, banks are so important in everyday life of people that it seems impossible to imagine life without a bank. Bank is strongly linked with currency’s concept as if a heart runs money into the society’s vessels; any change and chaos of this heart can paralyze the society. This huge and powerful entity plays an important role in all developed and underdeveloped countries as an influential power, authority or any power factor in all societies. Positive and effective activity of banks can be efficacious in the growth of economic sectors and productions per unit and indubitably enhance economic development in some areas. Most of the monetary exchanges are done by banks in today's world.

" Managing peoples’ life affairs and countries’ economic affairs require banks. It is possible to have a good influence on the decisions of users according to the importance of banks in modern societies by classifying the banks based on their financial health.


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In this study, we have used 36 independent variables that determine the financial health of banks. Each variable is divided into three groups which comprises of the least important, important and the most important, based on the degree of its importance to have data with better quality within the category. In this study, financial health classification in modeling of banks has been considered. Here, it is possible to identify effective factors in determining the financial health of banks with utilising the data mining tools, including the analysis of each independent variable. Decision tree-based method is selected to categorise due to the complexity of this issue. Although the decision tree-based methods have been used in various fields, they have been rarely used for classification of banks.

The structure of this article continuation is organised as follows: In the section 2, the proposed method steps for classification are described. The process of data mining involves data collecting, preprocessing and the quality of extracted factors affecting the classification of banks are described in section 3. Subsequently, it involves the classification results of banks and discussion on the results in section 4 and ends with collecting and presenting the suggestions in section 5.

ISLAMIC BANKING

The first modern experiment in Islamic banking can be traced to the establishment of the Mit Ghamr Savings Bank in Egypt in 1963. During the past four decades, however, Islamic banking has grown rapidly in terms of size and the number of players. Islamic banking is currently practiced in more than 50 countries worldwide. In Iran, Pakistan, and Sudan, only Islamic banking is allowed. In other countries, such as Bangladesh, Egypt, Indonesia, Jordan and Malaysia, Islamic banking co-exists with conventional banking. Islamic banking, moreover, is not limited to Islamic countries. In Islam, there is no separation between mosque and state. Business, similarly, cannot be separated from the Islamic religion. The Shariah governs every aspect of a Muslim’s religious practices, everyday life, and economic activities. Muslims, for example, are not allowed to invest in businesses considered non-halal or prohibited by Islam, such as the sale of alcohol, pork, and tobacco; gambling; and prostitution. In Islamic contracting, Gharar (uncertainty and risk) is not permitted, i.e., the terms of the contract should be well defined and without ambiguity. For example, the sale of fish from the ocean that has not yet been caught is prohibited. The prohibition of Gharar is designed" 31"K/,9,-3"3L,"M,.N":/1O"4,0-@",>K2103,P".-PQ"3LR?Q"."S,/1A?RO" @.O," 0-" ML0+L" 1-," @.0-?" at the expense of another is not sanctioned. Gambling and derivatives such as futures and options, therefore, are considered un-Islamic due to the prohibition of Gharar.

Ranking of Islamic Banking Efficiency Based on Decision Tree in Iran"

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More importantly, Muslims are prohibited from accepting or offering Riba. What constitutes Riba, however, is controversial and has been widely debated in the Islamic community. Some view Riba as usury or excessively high rate of interest. But the majority of Islamic scholars view Riba as interest or any pre-determined return on a loan. The basis for the prohibition of Riba in Islam may be traced to the common medieval Arabic practice of doubling the debt if the loan has not been repaid when due. This practice in its extreme form had led to slavery in medieval Arabia due to the absence of bankruptcy legislation that protects the borrower from failed ventures. Therefore, the prohibition of Riba can be viewed as part of Islam’s general vision in upholding a moralised economy. In Islamic economics, the lender should bear the risk of the venture with the borrower because it is deemed that neither the borrower nor lender is in control of the success or failure of a venture. Thus, a unique feature that differentiates Islamic banking from conventional banking, in theory, is its profit-and-loss sharing (PLS) paradigm. Under the PLS paradigm, the ex-ante fixed rate of return in financial contracting, which is prohibited, is replaced with a rate of return that is uncertain and determined ex-post on a profit-sharing basis. Only the profit-sharing ratio between the capital provider and the entrepreneur is determined ex-ante. (PLS) contracts, in general, allow two or more parties to pool their resources for investment purposes and to share the investment’s profit and loss. " The (PLS) paradigm is widely accepted in Islamic legal and economic literature as the bedrock of Islamic financing. Islamic bank financing, which adheres to the (PLS) principle, is typically structured along the lines of two major types of contracts: Musyarakah (joint venture) and Mudarabah (profit-sharing). Musyarakah contracts are similar to joint venture agreements, in which a bank and an

entrepreneur jointly contribute capital and manage a business project. Any profit and loss from the project is shared in a predetermined manner. The joint venture is an independent legal entity, and the bank may terminate the joint venture gradually after a certain period or upon the fulfilment of a certain condition.

Mudarabah contracts are profit-sharing agreements, in which a bank provides the entire capital needed to finance a project, and the customer provides the expertise, management and labour. The profits from the project are shared by both parties on a pre-agreed (fixed ratio) basis, but in the cases of losses, the total loss is borne by the bank.

Most theoretical models of Islamic banking are based on the Mudarabah and/or Musyarakah concepts of (PLS). There are, however, other financing contracts that are permissible in Islam but not strictly (PLS) in nature. Such financing contracts, for example, may be based on Murabaha (cost plus), Ijarah (leasing), Bai’ muajjal (deferred payment sale), Bai’ salam (forward sale), and Istisna (contract manufacturing) concepts. Murabaha financing is based on a mark-up (or cost plus) principle, in which a bank is

authorised to buy goods for a customer and resell them to the customer at a predetermined price that includes the original cost plus a negotiated profit margin. This contract is typically used in working capital and trade financing.


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Ijarah financing is similar to leasing. A bank buys an asset for a customer and then leases it to the customer for a certain period at a fixed rental charge. Shariah (Islamic law) permits rental charges on property services, on the precondition that the lessor (bank) retain the risk of asset ownership.

Bai’ muajjal financing, which is a variant of murabaha (cost plus) financing, is structured on the basis of a deferred payment sale, whereby the delivery of goods is immediate, and the repayment of the price is deferred on an instalment or lump-sum basis. The price of the product is agreed upon at the time of the sale and does not include any charge for deferring payments. This contract has been used for house and property financing.

Bai’salam is structured based on a forward sale concept. This method allows an entrepreneur to sell some specified goods to a bank at a price determined and paid at the time of contract, with the delivery of goods in the future.

Istisna contracts are based on the concept of commissioned or contract manufacturing, whereby a party undertakes to produce a specific good for future delivery at a pre-determined price. It can be used in the financing of manufactured goods, construction and infrastructure projects.

The acceptability of the above non-(PLS) modes of financing, however, has been widely debated and disputed because of their close resemblance to conventional methods of interest-based financing. Many Islamic scholars, including Pakistan’s Council of Islamic Ideology, have warned that, although permissible, such non-(PLS) modes of financing should be restricted or avoided to prevent them from being misused as a “back door” for interest-based financing. The Iranian financial system has gone through a structural change since 1984 when the central bank of the Islamic Republic of Iran officially adopted the interest free banking system.

PROPOSED METHOD

Figure 1 portrays the general framework of the proposed method is to classifying the bank in this study. This method includes the data mining steps and decision tree modeling for the category. Data are preprocessed from the accepted banks of stock exchange in the first step of data mining. This is done by obtaining 36 financial ratios considered as independent variables in this research. Classification will be more useful by classifying the degree of importance each of these variables. Next, a feature selection algorithm is applied to set the data to extract the main variables affecting the classification of the banks from among all the data set variables. One model is presented to classify the banks according"to the decision tree- based financial health in the modeling step.


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Figure 1: Data Mining Process

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"THE DECISION TREE

Decision tree is one of the most useful methods used for inductive inference. Decision tree is a monitored and controlled learning method implemented by using a division and resolution strategy. In this way, the learned function is displayed as a decision tree which is sometimes turned into a set of if-then rules to increase the degree of human readeptability. These algorithms create a tree based on the learning set, in which each internal node shows a test on an attribute; each branch represents the conclusion of the assessment and each label maintains a class. A decision tree consists of a series of internal decision nodes, terminal nodes and root. When a decision tree is used for classification, it will be known as classification tree. Superiority criterion of a separator can be determined by impurity measure. A pure isolator divides the data into corresponding sub-branches, so that each branch contains data belonging to a class. Decision tree is built from top to bottom and can be used for classifying the data which are to betested. This algorithm is a conspicuous search in which the previous selections will not be reviewed. Decision trees have many applications in the computer systems and one of them is related to data classification. Decision tree construction is an important data mining problem. Over the last decade, decision tree construction over disk resident datasets has received considerable attention (Jin and Agrawal, 2003). Furthermore, classification is especially attractive in a data mining environment for several reasons. First, due to their intuitive representation, the resulting classification model is easy to be assimilated by humans. Second, classification trees are non-parametric.


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Classification tree construction algorithms do not make any assumptions about the underlying distribution and are thus ideally suited for exploratory knowledge discovery. Third, classification trees can be constructed relatively fast compared to other methods. Last, the accuracy of classification trees is comparable or superior to other classification models (Gherka, Ramakrisnan and Ganti, 2000).

(Gehrka et al., 1999) introduce a new scalable algorithm (BOAT) to construct decision trees for large training databases. (BOAT) is faster than the best existing algorithms by a factor of three while constructing exactly the same decision tree, and can handle a wide range of splitting criteria. Beyond improving performance, (BOAT) enhances the functionality of existing scalable decision tree algorithms in two major ways. First, (BOAT) is the first scalable algorithm that can maintain a decision tree incrementally when the training data set changes dynamically. Second, (BOAT) greatly reduces the number of database scans, and offers the flexibility of computing the training database on demand instead of materializing it, as long as random samples from parts of the training database can be obtained. In addition to developing the (BOAT) algorithm and proving it correct, they have implemented it and presented a thorough evaluation that demonstrates its scalability, incremental processing of updates, and efficiency over existing algorithms. (Zhou et al., 2008) presented a (KD-tree) algorithm capable of achieving real time performance on the GPU. The algorithm builds (KD-trees) in (BFS) in order to exploit the large scale parallelism. The constructed (KD-trees) are of comparable quality to those built by off-line (CPU) algorithms. They also demonstrated the potential of their (KD-tree) algorithm in three applications involving dynamic scenes: (GPU) ray tracing, (GPU) photon mapping, and point cloud modeling (Zhou et al., 2008). Moreover, using high-quality (KD-tree) is essential for achieving interactive ray tracing performance. Therefore, the goal is to build a (KD-tree) as fast as possible minimizing its quality degradation. A typical (KD-tree) construction proceeds in a top-down fashion by recursively splitting a current node into two sub-nodes using the following sequence of tasks. • Generate split plane candidates at some locations; • Evaluate cost function using (SAH) at each location; • Pick the optimal candidate (with lowest cost) and perform split into two child nodes; • Pass over geometry to distribute it among children; • Repeat recursively (Lawrence and Wright, 2001).

(CART) is an increasingly popular form of statistical analysis available through widely used statistical packages, such as S-Plus. (CART) operates by recursively splitting the data until ending points, or terminal nodes, are achieved using preset criteria. (CART) therefore begins by analysing all explanatory variables and determining which binary division of a single explanatory variable best reduces deviance in the response variable. A wide variety of classification options are available for image processing, and no single classification solution will always perform best. Incorporating ancillary data into rule-based classifications, however,


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has been shown to be an effective approach in certain circumstances. We developed and demonstrated a method for creating and executing such a classification system without extensive a priori expert knowledge. This method, based on (CART) analysis, was easily implemented using commonly available image processing and statistical software (Jin and Agrawal, 2003). (Chen et al., 2002) dealt with the activity-sensitive clock tree problem. We have presented the method of determining the control signals as such that their transitions are reduced. By using modules’ activity information, the clock tree construction algorithm and local uncaring technique have been introduced for power savings. It has been shown that node difference plays an important role in low-power clock tree design. Given a set of pins and a set of obstacles on a plane, an obstacle-avoiding rectilinear Steiner minimal tree (OARSMT) connects these pins, possibly through some additional points (called Steiner points), and avoids running through any obstacle to construct a tree with a minimal total wire length. The (OARSMT) problem becomes more important than ever for modern nanometer IC designs which need to consider numerous routing obstacles incurred from power networks, perorated nets, IP blocks, feature patterns for manufacturability improvement, antenna jumpers for reliability enhancement, etc. Consequently, the (OARSMT) problem has received dramatically increasing attention recently. Nevertheless, considering obstacles significantly increases the problem complexity, and thus most previous works suffer from either poor quality or expensive running time (Lin et al., 2007). (Andrew and Morgan 1986) described the digraph method of fault tree construction and its application to the process stream of a butane vaporizer. It is shown that an accurate, well-structured fault tree can be produced for the usage of a process system that incorporates a number of control loops.

VARIABLES SUBSET SELECTION ALGORITHM

If we can study variables group instead of separately, we will get more data. Some data table columns may mistakenly be deleted or some variables may be considered more useful when we usually examine the variables separately, but they are weak in terms of predictive power of variables. Variables subset selection algorithm includes three steps in this study as follows:

Screening: it includes cancellation of less important variables (variables that do not have useful information for estimating or difficult data samples).

Classification: it consists of sorting the remaining variables and assigning them to be rated.

Selection: identifying features important subsets to apply in the model. Figure 2 shows the variables subset selection algorithm general form.


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Figure 2: Variables Subset Selection Algorithm General Form

DATA MINING PROCESS

Usable data are extracted by the financial lists and attached finical notes. The mentioned financial statements are obtained from the websites of www.Codal.ir and www.Rdis.ir. This research statistical society is consisted of all listed bank in Tehran Stock Exchange and sampling

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is based on random deletion method. In current study the sample society includes all listed banks with the availability of financial data; including 9 banks for 4 years; a total of 36 years, during 2008 to 2011.

DATA ANALYSIS METHOD

At first, data analysis method begins with the financial ratios calculation using the excel software and following banks are classified by decision tree modeling to classify the health of the banks. On the other hand, the research has faced up with limitations due to the lack of access to all financial statements of banks between the years of 2008-2011 and lack of sufficient data on financial statements and attached notes of financial statements to calculate the ratios. Hence, the problem provides us with a useful model by "checking the effective variables in classifying the banks". Thirty-six variables are above the minimum amount of importance according to the Table 1.

Table 1: Variables of the Study

Num

ber

Description of the Ratios

Impo

rtanc

e

Status

1 Nonperforming assets to total assets 1 Lower is better

2 Loans and commitments to total deposits 2 higher is better

3 Core deposits to total deposits 1 higher is better

4 Total operating expense to total operating income 3 Lower is better

5 Net loans to total assets 2 higher is better

6 Other real estate owned to total assets 1 higher is better

7 Loans to insiders to net loans 1 Lower is better

8 Total securities to total assets 1 higher is better

9 Undivided profit and capital reserve to total assets 2 higher is better

10 Return on average total assets 3 higher is better

11 Commitments to total assets 2 Lower is better

12 Jumbo time deposits to total deposits 1 higher is better


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13 Net loans to total deposits 1 higher is better

14 Total nonperforming and restructured loans to gross loans 1 Lower is better

15 Nonperforming loans to net loans 1 Lower is better

16 Jumbo time deposits to net loans 1 higher is better

17 Return on equity 3 higher is better

18 Return on total assets 3 higher is better

19 Total assets 2 higher is better

20 Cash and due to total assets 1 higher is better

21 Restructured loans to gross loans 1 Lower is better

22 Personnel expense to total operating income 3 Lower is better

23 Nonperforming loans to primary capital 2 Lower is better

24 Total interest expense to total operating income 3 Lower is better

25 Interest rate swaps to total deposits 1 Lower is better

26 Nonaccrual loans to gross loans 1 Lower is better

27 Noninterest income to total operating income 2 higher is better

28 Earnings assets to total assets 3 higher is better

29 Provision for loan and lease loss to total assets 2 Lower is better

30 Total operating income to total assets 3 higher is better

31 Interest-bearing deposits to total deposits 1 higher is better

32 Nonperforming loans to total assets 3 higher is better

33 Total interest expense to total assets 2 Lower is better

34 Allowance for loan and lease loss to net loans and leases 3 higher is better

35 Past due loans to gross loans 1 Lower is better

36 Public deposits to total deposits 1 Lower is better


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DECISION TREE BASED CLASSIFICATION MODEL

Decision tree is one of the powerful and common tools to classify and predict. In this way, classification is done within the rules and answers finding for questions and questioning as well as answering process will continue to complete the classification and create the decision tree and is used to predict the model after classifying it. Generally, the decision tree creation is composed of two stages: Growth phase and tree creation include links and branches of the links and is consist of low significance independent variables assigned to significant groups based on the target variable (dependent). Branching includes choice of failure / break point by choosing a variable that is able to select the next best and new branches. The stopping and pruning step of the tree is accompanied with the aim of minimizing the prediction error, stop the rules calculating the development of branches in the nodes and pruning involves removing of the branches having little effect on estimated values resulted in the final model. Selection of the failure / break point and branch point creation in the tree are important. There are different methods for selecting the point of failure/break. The way chosen in this study is called card method. Indexes card is in dual implementation algorithm and is only branched according to the independent variable. Each parent node is divided into two child sub-groups based on the similarity between its members. Consequently, the members of each node are more pure than their parents.

IMPLEMENTATION RESULTS

The suggested banks classification model was fitted to the obtained data sets. Figure 3 shows the pruned tree structure of the problem. Some examples of the rules obtained from the tree in Table 2 are presented. These rules are in the form of "if - then", it means that each longitudinal direction from beginning to end creates a rule for estimating the target variable by the sub-conjunction of the rule.

Figur 3: Decision Tree


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X10: Return on average total assets. X1: Nonperforming assets to total assets. X7: Loans to insiders to net loans. X6: Other real estate owned to total assets.

Table 2: Obtained Rules from the Tree

Node x10:

If x10=1

Then, the x1 node occurs

Node x 7:

If x7=3

Then, the x6 node occurs

The resulted classification based on the rules derive from the decision tree which is presented in Table 3.

Table 3: Classification of sample society

Cluster Number: Cluster 1 Cluster 2 Cluster 3

Year: 2008 2009 2010 2011 2008 2009 2010 2011 2008 2009 2010 2011

EGHTESAD NOVIN

X X X X

PARSIYAN X X X X

KARAFARIN X X X X

MELAT

X X X X

PASARGAD X X X X


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POST BANK X X X X

TEJARAT

X X X X

SINA X X X X

SADERAT X X X X

Table 4: Presents More Details of the Study Findings.

Table: The Results of The Study

Cluster Number: Cluster 1 Cluster 2 Cluster 3

EGHTESAD NOVIN 4

PARSIYAN 4

KARAFARIN 4

MELAT

4

PASARGAD 4

POST BANK

4

TEJARAT

4

SINA

4

SADERAT

4

CONCLUSION

In this study, a nonparametric method based on decision tree is proposed to classify and categorize the financial health of the banks. Model input of the data mining process is extracted according to the related data to the banks listed in the Tehran Stock Exchange. The results of this model are useful from several perspectives. The first view helps to identify weaknesses in the banks and draws a realistic picture of it. In the second view, users can use more effective


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variables in determining the financial health of the banks and useful decisions are made to achieve the desired goal based on it.

REFERENCES

Andrews, J.D. and Morgan, J.M., (1986). Application of The Digraph Method of Fault Tree Construction to Process Plant. Reliability Engineering, Vol. 14, No. 2, pp. 85-106.

Chen, C., Kang, C., Sarrafzadeh, M, (2002). Activity-Sensitive Clock Tree Construction for Low Power, Proceedings of The International Symposium on Low Power Electronics and Design.

Gehrka, J., Ganti, V., Ramakrishnan, R., Loh, W, Y, (1999). BOAT-Optimistic Decision Tree Construction, Vol. 28, No. 2, pp.1-12.

Gherka, J., Ramakrisnan, R., Ganti, V, (2000). Rainforest- A Frame Work Fast Decision Tree Construction of Large Datasets, Data mining and Knowledge Discovery, Vol. 4, pp.127-162.

Jin, R., Agrawal, G (2003). Efficient Decision Tree Construction on Streaming Data, Proceedings of The Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.

Lawrence, R, L., Wright, A, (2001). Rule-Based Classification Systems Using Classification and Regression Tree (CART) Analysis, Photogrammetric Engineering & Remote Sensing Vol. 67, No. 10, pp.1137-1142.

Lin, C, W., Chen, S, Y., Li, S, F., Chang, Y, W., Yang, C, L, (2007). Efficient Obstacle-Avoiding Rectilinear Steiner Tree Construction, Proceedings of The International Symposium on Physical Design.

Zhou, ken., Hou, Q., Wang, R., Guo, B (2008). Real-Time KD- Tree Construction on Graphics Hardware. ACM Transactions on Graphics Journal (TOG), Vol. 27, No. 5, pp. 1-12.


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ISLAMIC FINANCE FOR SMALL AND MEDIUM-SIZED ENTERPRISES

Abdulaziz M Abdulsaleh

ABSTRACT

There is no doubt that access to finance is of vital importance for the ongoing and sustainable growth and profitability of small and medium-sized enterprises (SMEs). In this context, the main motive of this paper is that considering the constraints that hinder SMEs access to credit such as; inadequate collateral, insufficient legal status, and high transaction costs, it is argued that by recognising its principles including avoidance of interest (riba), risk-sharing, along with the availability of credit for primarily the purchase of real goods and services, and restrictions on the sale of debt, short sales, excessive uncertainty (gharar), and gambling, Islamic finance methods are more suitable for financing (SMEs). Hence, the purpose of this paper is to review the literature on the main financing modes of (SMEs) offered by Islamic banks and other Islamic financial institutions.

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INTRODUCTION

As recently in the 1970s, Islamic finance has arose as a new trend with promising potential in the field of finance. The rapid growth of Islamic finance is not confined to Islamic countries as it has also spread to non-Muslim countries that have sizeable Muslim populations, including the US, the UK and Australia. According to McKenzie (2011) since the mid of 1990s the financial assets of the Islamic finance industry had grown from USD 150billion to approximately USD1041 billion in 2009. The author further asserts that this industry is expected to sustain a growth rate of 10 to 15 percent per annum over a number of upcoming years. It is argued in the Islamic financing literature that many of the elements of microfinance are in accordance with the broader objectives of Islamic finance. In this context, (Obidullah and Lattif 2008) believe in the possibility of a successful marriage between the two disciplines. They support their belief by clarifying some aspects which these two disciplines have in common. According to authors both Islamic finance and microfinance advocate entrepreneurship as well as risk sharing between the financier and the entrepreneur. Also, both disciplines, the authors add, prioritize developmental and social goals by encouraging the participation of the poor in the economic activities.


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Additionally, (Segrado 2005, p. 5) lists a number of principles that Islamic finance shares with microfinance including: • Prohibition of all forms of economic activities which are morally or socially injurious. • Egalitarian approach (no restriction to any category of clientele). • Focus on the well-being of the community as a whole, concentrating on the poor, destitute deprived sections of the society. • Aim at social justice. • Advocacy of entrepreneurship. • Advocacy for financial inclusion through partnership finance. • Participatory approach. • Risk sharing.

In comparison with conventional methods of financing and by considering the participation nature of Islamic financing that encourages the client loyalty. Islamic financing methods are believed to have greater suitability and pertinences for (SMEs). This can be attributed to the ongoing dialogue between the two parties (the financier and the entrepreneur) which, in essence, improves the decision-making process. As a result, a superior outcome of the business decision-making can be expected as the two parties are working together rather than working in isolation each. (Elasrag 2011) emphasized that unlike conventional interest-based finance which benefits the financier, Islamic finance offers unique financing techniques for (SMEs) that ensure justice for both parties in the contract. In the same vein, (Ibrahim 2003) argued that Islamic financing methods are better suited in satisfying the financial needs of (SMEs). The focus in Islamic financing and investment, he explains, is on the transaction itself instead of the creditworthiness of the partner. As such, entrepreneurs are granted funding without an obligation to them to provide strict securities or collateral which (SMEs) often lack. He adds that as profit and loss sharing is pivotal in Islamic finance, any securities or collateral demanded by the financier is not against the risk of loss, it is rather against the fraudulent or repayment evasion. A salient example of Islamic finance system that can be cited is that of Sudan where the entire financial system has been officially converted into an Islamic financial system. According to (Ibrahim 2003), the Sudanese Islamic Bank, opened in 1994, provided financing for up to 500 (SMEs) by the end of its first year in operation. These enterprises were financed through Musharakah, Mudarabah and Murabahah with a percentage of 17, 6 and 74 respectively. A decade earlier, in 1993, Faisal Islamic Bank of Sudan was established. During the fiscal year of 1993–94, the number of (SMEs) financed by the bank was 1,400, of which (100%) was financed by Murabaha. The Agricultural Bank of Sudan and Islamic Co-operative Development Bank are examples of other financial institutions that offer Islamic finance to (SMEs) in Sudan. Prior to reviewing the literature on Islamic financing methods applicable for SMEs, the following section briefly presents the definition and principles of Islamic finance.

Islamic Finance For Small and Medium Sized Enterprises

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THE DEFINITION OF ISLAMIC FINANCE

Islamic finance can be defined as “.. a financial service principally implemented to comply with the main tenets of Sharia (or Islamic law)” (Gait and Worthington, 2007, p. 4). Another definition by (Warde 2000, p. 5) stated that “Islamic financial institutions are those that are based, on their objectives and operations, on Holy Quran’s principles”. In the latter definition it can be noted that the productions of Islamic finance can be offered by other firms than banks as long as those firms employ Sharia principles. The main sources of Sharia are six. Those sources are Holy Quran, Hadith, Sunna, Ijma, Qyias and Ijtihad. The first source of Sharia and the most important one is the Holy Quran. The Holy Quran is the noble revelation given to the Prophet Muhammad Sallallahu Alai Wa Sallam (SAW). Second in ranking of Sharia sources is Hadith which is the narrative related to the deeds and utterances of the Prophet Muhammad SAW (Hadith is usually classified as a part of Sunna). Third is Sunna which refers to the habitual practice and behaviour of the Prophet Muhammad SAW during his lifetime. Ranking fourth among other sources of Sharia, Ijma indicates the consensus among religion scholars about specific issues that are not directly addressed in either the Holy Quran or the Sunna. Fifth is Qyias which involves the use of deduction by analogy and comparing the case at hand (must be not referred to the Holy Quran or the Sunna) with another case referred to the Holy Quran and the Sunna in order to provide an opinion on that first case. Finally, Ijtihad is an independent reasoning of jurists regarding the applicability of certain cases not mentioned neither in the Holy Quran nor the Sunna.

THE PRINCIPLES OF ISLAMIC FINANCE

Islamic financial institutions are similar to their conventional peers in terms of that they are “private profit-seeking business enterprises that operate according to the market mechanism” (Al-Jarhi, 2004). However, the philosophy of Islamic finance is completely different from those of conventional financial institutions with respect to money and business matters.To achieve its goal that is to be an ethical, indigenous, and equitable mode of finance, Islamic finance is governed by the principles of Sharia which encompasses of the ethos and value system of Islam. The main principles on which any Islamic financial systems is found are as follows.

Prohibition of Riba (usury or interest)

The prohibition of Riba (usury or interest) is the most important principle of Islamic finance. Riba is the Arabic word for any growth or increase, large or small, in the repayment made by the debtor to the lender for the use of money (Siddiqi, 2004; Shanmugam and Zahari, 2009). Muslim scholars have interpreted Riba to be defined as any fixed or guaranteed interest payment on cash


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advances or deposits (Mahmood, 2004). As such, any financial transaction involves interest or predetermined payment over and above the actual amount of the loan is strictly prohibited in the Islamic financial system (Gait and Worthington, 2007).

The prohibition of Gharar (risk and uncertainty)

Gharar is an Arabic term that can be translated as risk, uncertainty or deception. Gharar is defined as “… the sale of probable items whose existence or characteristics are not certain, due to the risky nature which makes the trade similar to gambling” (El-Gamal, 2000, p.7). Gharar exclusively applies to cases of doubtfulness or uncertainty, as in the case of not knowing whether something will take place or not (Al-Dhareer, 1997). In this sense, Gharar is very similar to information asymmetry. In spite of the fact that there is no explicit statement in the Quran that forbids Gharar, it is well accepted and believed that it is prohibited (Al-Saati, 2003).

The prohibition of forbidden assets

One of the fundamentals of Islamic finance is the prohibition of dealing with certain products and services such as alcohol, drugs, pork products, gambling and pornography (Austrade, 2010; Gait and Worthington, 2007). As such, Islamic financial institutions can engage in or finance only activities that do not violate the rules of Sharia and are permitted by Islam. In order to achieve this objective, each Islamic financial institution should have an independent Sharia supervisory board (Shanmugam and Zahari, 2009) to promote ‘ethical’ investments that do not adversely affect individuals and society through the violation of religious prohibitions.

Sharing of risks and profits

Based on this principle Islamic finance mixes capital and skills as well as and shares the risk and the resultant profit or loss of the business. Here, according to (Ibrahim 2003), only the profit sharing ratio, not the rate of return itself, is predetermined. In the case of a loss, the financier bears the risks of loss whereas the entrepreneur losses his/her time and effort (Gait and Worthington, 2007). This mechanism of profit-loss sharing is believed to encourage people to become partners and work together rather than to enter into a creditor–debtor relationship.

ISLAMIC METHODS OF FINANCE FOR SME’s

In this section the most common Islamic finance methods for SMEs as practiced by Islamic banks and other financial institutions are discussed. These financing methods range from most


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popular methods such as; Musharakah, Murabahah, and Mudarabah to less popular ones such as; Ijarah, BaiSalam, Baimuajjall, and QuardHasan.

Musharakah

Musharakah is the Arabic translation of partnership. Musharakah is a mode of Islamic finance which can be defined as “… a form of partnership where two or more persons combine either their capital or labour together, to share the profits, enjoying similar rights and liabilities” (Al-Harran, 1993, p. 47). In this form, the profits are shared according to a pre-determined agreed ratio, however, in the case of loss it will be shared based on capital contribution ratio. Additionally, In Musharakah contract all partners are entitled to have a role in the management of the project. According to (Lewis and Algaoud 2001) Musharakah contract can be either permanent or a diminishing contract. In the former, which may last to limited or unlimited period depending on the original agreement, annual equal shares of the profit/loss are ensured for both parties based on pre-agreed deal. In the latter, however, capital is not permanent since the financier receives profits on a regular basis diminishing his/her equity. Consequently, this will gradually increase the total capital of the client till he/she becomes the only owner of the project. The discovery of (Ibrahim 2003) highlighted some advantages of Musharakah contracts. First of all, compared to the rate of return of conventional finance (interest rate), rates of return for the capital provider in Musharakah are large, thus, financially, for the financing through Musharakah is profitable in the financing institution. Similarly, the rate of return of the partner’s capital is slightly higher than his/her share in the total capital even if this share is less than the financier’s. This is because the inclusion of management effort in Musharakah. Another advantage for the entrepreneur is that since Musharakah does not require strict collateral guarantees so that it does not have to leave the entrepreneur with a heavy burden of debts or any other obligations. In addition, Musharakah is a suitable technique of financing for both fixed and working capital. Nevertheless, under Musharakah contract, some ambiguities may exist regarding the title to assets in case of default or dissolution. In order to partially offset the increased risk in such situation, the procedure which could be taken is to register the project’s assets under the co-ownership concept provided by a partnership or corporation arrangement (Samad et al., 2005). Yet, capital providers especially banks may prefer to opt for other Islamic financing methods such as Murabahah.

Murabahah

Among all Islamic financing modes, Murabahah is the most distinct and the most popular one. Under Murabahah contract the financier (often Islamic bank) purchases or imports certain goods


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or commodities (assets or raw materials) ordered by the client and then resells them to the entrepreneur after adding a negotiated profit margin (Dhumale and Sapcanin, 1999). Under this contract the payment is due in installments. It can be inferred that Murabahah transaction entails two contracts (Al-Jahri and Iqpal, 2001). The first contract is that one between the financier (usually the bank) and the supplier of the goods/commodities. The second is between the financier and the client who applied for the goods/commodities. The fundamental principles that characterise Murabahah contracts are summarised in (Gait and Worthington, 2007). First, the goods/commodities must be classified clearly and identified on the base of accepted standards and must be provided by the time of sale. Second, at the time of sale, goods/commodities must be owned completely by the financier. Third, the entrepreneur must be informed of the cost price at the sale point. Finally, both the time of goods/commodities delivery and the due date of payment must be clearly specified. In addition, another key characteristic of Murabahah transaction is that beyond the time of sale the ownership of the goods/commodities remains with the financier until the last payment made (Samad et al., 2005). In a study jointly found by the United Nation Development Programme and the World Bank on the Islamic microfinance feasibility conducted by (Dhumale and Sapcanin 1999) Murabahah was found more practical and the most suitable financing technique that can be provided by Islamic finance institutions. They (Dhumale and Sapcanin, 1999) attributed this to the fact that the buy-resell model which allows repayments in equal installment is easier to administer and monitor. In the same vein, (Hassan and Dicle 2005) and (Khan and Ahmed 2001) consider the most important advantage of Murabahah is that since the financier collateralises the debt beyond the good/commodity itself, as such, the risk of loss becomes much less than the risk of credit transaction in conventional transactions. In addition, (Ibrahim 2003) asserts that Murabahah contracts will ensure that the client will have the intended goods/commodities, so thus avoiding the usage of the money for a different purpose which is usually the case in the conventional loan contracts. Moreover, unlike Musharakah contract and as mentioned earlier, in Murabahah there is no ambiguity concerning title to the assets as they remain owned by the financier till the payment is completed.

Mudarabah

(Gafoor 2006) described Mudarabah contract as profit sharing and loss absorbing rather than profit and loss sharing contract. According to (Al-Jahri and Iqpal 2001) Mudaraba is a contract between two parties; a capital owner and an investment manager, under which profit is distributed in accordance to a ratio that is pre-agreed between the two parties at the time of the contract, whereas, financial loss is borne solely by the capital provider and the manager losses his/her effort and the expected profit. In other words, Mudaraba refers to two parties which are involve together to establish a project whereby one party (individual or bank) provides the capital needed and plays no further role in the project while the other (entrepreneur) offers his/her skills, experience and effort. Profits are then divided between the two parties on the base


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of pre-determined ratio. In the case of loss, however, the financier entirely bears the financial loss and the entrepreneur bears the operating losses and receives no reward for his/her effort. One exception that the entrepreneur becomes liable for the amount of capital invested is in the case of negligence and breaching of the terms of the contract (Abdulrahman, 2007). (Segrado 2005) has categorized Mudarabah contracts into three categories. First category is demand deposits in which deposits are not restricted, payable on demand and do not share any profits. Second category is that of mutual investment deposits where these deposits are combined with the bank’s money with the aim to participate in mutual investment transactions conducted by the bank. Under such deposits, the percentage of profit is fixed at the end of the financial year of the bank. The third of these categories is special investment deposits under which deposits will be invested in a specific project or investment in accordance with the depositor’s request. In this case the depositor will be entitled to receive profits and is liable for the losses, given that the bank is not negligent or in default. At the end of the deposit period, the bank receives its share of profit against its contribution of experience and management, while the depositor receives his/her share of profit as a capital share contributor. Due to agency issues accompanied with it, Mudarabah has been perceived as a risky product. As entrepreneurs usually do not keep track records of financial statements (Sergado, 2005; Abdulrahman, 2007) it is difficult to determine the actual profit to be shared between the two parties. Additionally, (Warde 2000) concluded that Mudarabah contract has been often associated with ethos hazard and adverse selection. Part of the reason for this is because honesty, transparency and trustworthiness presumably characterise the entrepreneur who cannot be guaranteed. As such difficulties are likely to be unavoidable in Mudaraba contracts, (Segrado 2005) suggeststed that specific training to overcome these issues is needed, thus, he confirmed that Mudaraba mode might be more suitable for (SMEs) with a longer profit cycle.

Ijarah

Literally Ijarah means to give something on rent (Lewis and Algaoud, 2001). Ijarah can be defined as “… a contract under which the Islamic financial institution buys and leases out an asset or equipment required by its client for a rental fee” (Ahmad and Ahmad, 2007, p. 254). Depending on the nature of the asset and the lessee’s requirements the lease duration varies from three months to five years or more. Said et. al. (n.d.) clarifies the basic rules of Ijarah. They explains that during the period of lease, which must be determined in clear terms at the time of contract, all liabilities of ownership remain in the hands of the lessor who is responsible for its maintenance so that it continues to give the service for which it was rented. The authorsadded that the asset must be used for the purpose identified in the contract unless no specific purpose for using the asset is identified in the agreement. In that case the asset can be used for any purpose for which it is used in normal course. In addition, the lessee is liable to compensate the lessor for any damage to the leased asset caused by any misuse or negligence.


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There are two types of Ijarah contract. The first is Ijarah contract ending with purchase which gives the lessee the choice to purchase the asset at the end of the lease period. The second is the one under which is known as benefit arising from the leased asset that is made available in return for the lesser whereas the ownership of the asset itself remains untransformed (Ahmad and Ahmad, 2007).

Baisalam

“Baisalam is a sale contract in which the price is paid in advance at the time of contracting against delivery of the purchased goods/services at a specified future date” (Iqbal and Molyneux, 2005, p. 25). According to (Hassan and Dicle 2005) in salam transactions it is required that goods/services, payment, and delivery terms to be identified in detail. As for the payment, the authors further explain, it has to be done in the time of the contract. The legal requirements of baisalam were discussed by (Gait and Worthington 2007). According to them these requirements are; (i) the commodities sold should not be available at the time of the contract; (ii) the quality and quantity of goods must be known; (iii) the time and location of delivery for the commodities should be defined; and (iv) at the time of contracting the price should be completely paid.

Baimuajjal

(Gait and Worthington 2007, p. 17) defined this mode of Islamic finance as “… a sale on a deferred payment basis that allows business or individuals to receive products now and pay for their value in the future”. Fundamentally, in such contract three separate agreements are included (Shanmugam and Zahari, 2009). In the case of real property, the first agreement details the supplier’s purchase of the property from the developer. In the second agreement, the property is to be sold to the client by the supplier. The third agreement stipulates that the supplier can sell the property in the event of default by the client.

QardHasan

Qardhasan or a “benevolent loan” which is perceived to be a "pure" form of Islamic finance. Qardhasan is “… a gratuitous loan given to needy people for a fixed period without requiring the payment of interest or profit” (Farook, 2007, p. 47). This loan can be used for different purposes for example, education, marriage, or housing. Under such arrangement the recipient is only required to repay the principal amount loaned. Additionally, Qardhasan loans are very secure since the borrower can be subjected to a penalty in case of delay in repayment. Moreover, it is acceptable for the lender to demand assets as collateral and charge administrative expenses on the loan (Obaidullah, 2005).


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CONCLUSION

It is emphasized that (SMEs) access to finance is one of the dynamic factors of enabling them to accomplish their role in economic and social development. Given the more favourable principles of Islamic finance which emphasize the transaction itself rather than the partner’s credit worthiness through the prohibition of interest/usury, risk sharing, avoiding financial transactions that involve uncertainty or speculation, and disbursement of collateral free loans, this paper promotes Islamic financing methods’ appropriateness and uniqueness for financing (SMEs). In order to achieve this, the paper is initiated by identifying Islamic finance as well as its basic principles before going beyond and reviewing the literature on the main Islamic financing methods which are applicable to (SME).

REFERENCES

Abdulrahman, A. (2007). Islamic microfinance: A missing component in Islamic banking. Kyoto Bulletin of Islamic Area Studies, 1(2), 38-53.

Ahmad, A. F., & Ahmad, A. B. R. (2007). Islamic micro and medium sized enterprises (MMEs) finance: The case study of Australia. Paper presented at the The First International Conference on "Inclusive Islamic Financial Sector Development: Enhancing Islamic Financial Services for Micro and Medium Sized Enterprises, Negara Brunei Darussalam.

Al-Dhareer, S. (1997). Al-Gharar in contracts and its effects on contemporary transactions: Islamic Research and Training Institute, Islamic Development Bank, Jeddah.

Al-Harran, S. A. S. (1993). Islamic finance: Partnership financing: Pelanduk Publications.

Al-Jarhi, M. A. (2004). Islamic banking and finance: Philosophical underpinnings. Paper presented at the Islamic Banking and Finance: Fundamentals and Contemporary Issues, Brunei.

Al-Jarhi, M. A., & Iqbal, M. (2001). Islamic banking: Answers to some frequently asked questions. Islamic Development Bank & Islamic Research and Training Institute Occasional paper, Occasional paper( 4).

Al-Saati, A. (2003). The permissible Gharar (risk) in classical Islamic jurisprudence. Islamic Economics, 16(2), 3-19.

Austrade. (2010). Islamic finance - Financial services Retrieved from http://www.austrade.gov.au/PerformSearch.aspx?ArticleID=4345&ModuleID=8367&Keywords=Islamic%20finance&SiteSection=&SiteSectionDescr.


http://www.austrade.gov.au/PerformSearch.aspx?ArticleID=4345&ModuleID=8367&Keywords=Islamic%20finance&SiteSection=&SiteSectionDescr

http://www.austrade.gov.au/PerformSearch.aspx?ArticleID=4345&ModuleID=8367&Keywords=Islamic%20finance&SiteSection=&SiteSectionDescr

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Dhumale, R., & Sapcanin, A. (1999). An application of Islamic banking principles to microfinance. A study by the Regional Bureau for Arab States, UNDP, in cooperation with the Middle East and North Africa Region Group: The World Bank.

El-Gamal, M. (2000). A basic guide to contemporary Islamic banking and finance: Rice University, Houston.

Elasrag, H. (2011). Activating the role of Islamic finance in the development of small and medium enterprises. (MPRA Paper No. 34398). Retrieved 12-07-2012, from Munich University Library http://mpra.ub.uni-muenchen.de/34398/

Farook, S. (2007). A standard of corporate social responsibility for Islamic financial institutions: A preliminary study. Paper presented at the First International Conference on "Inclusive Islamic Financial Sector Development: Enhancing Islamic Financial Services for Micro and Medium Sized Enterprises, Negara Brunei Darussalam.

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Gait, A., & Worthington, A. C. (2007). A primer on Islamic finance: Definitions, sources, principles and methods. University of Wollongong, School of Accounting and Finance Working Paper Series No. 07/05, 2007.

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McKenzie, D. (2011). Islamic finance. Retrieved from http://www.thecityuk.com/assets/Uploads/Islamic-finance2011.pdf. Obaidullah, M. (2005). Islamic financial services: Islamic Economics Research Centre, Jeddah.

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Segrado, C. (2005). Islamic microfinance and socially responsible investments, Case study. University of Turin.

Shanmugam, B., & Zahari, Z. R. (2009). A primer on Islamic finance.

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http://www.thecityuk.com/assets/Uploads/Islamic-finance2011.pdf

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The growth of Islamic banks in Indonesia has shown a remarkable development especially after the monetary crisis occurred in 1998. This crisis has opened some people and government eyes

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to have business in finance without using interest rate. However, Islamic finance which is based on the mechanism of profit sharing leads to business in natural and normal ways.

Some Islamic banks in the form of full fledged system and Islamic units have been established in numbers and size. This phenomenon may be supported by the Act and regulations that are conducive to establish the Islamic banks to grow faster and stable. On the other hand, some problems that can be threats to the development and growth of Islamic banks are the absence of Islamic money market, double taxation on murabahah (selling activities) and high interest rates. Currently, these may have been solved by the government supports and economic conditions. This paper tries to analyze the effects of conversion from Islamic unit to full fledged Islamic banking system. It utilized two Islamic banks (Bank Bukopin and Bank Rakyat Indonesia) which underwent Islamic units then converted them to full fledged Islamic banking system. Besides, nowadays there are additional four Islamic banks under full fledged Islamic banking system (three directly established full fledged such as Bank Panin Bank Syariah, Bank Victoria Syariah, Bank Central Asia Syariah (BCA Syariah) and Maybank Indonesia Syariah as well as from Islamic units (Bank Negara Indonesia Syariah, Bank Jabar dan Banten Syariah dan Maybank Indonesia Syariah). The research period covered from 2005 until mid of 2009, then it continued until mid of 2011 for spin-off analysis effect. Some variables are analyzed further, such as total asset, deposits, net income (semi annual), number of branches and stock price. The analyses employed are event study, benchmarking analysis and Wilcox on test.

ISLAMIC BANKS IN INDONESIA

The history of Islamic banks in Indonesia was formally in 1992 when Bank Muamalat was established. However, before it was established, there were three Islamic rural banks (Bank Pekreditan Rakyat Syariah – BPRS) that had a permission to set up Islamic rural banks, namely BPR Dana Mardhatilla, BPR Berkah Amal Sejahtera and BPR Amanah Rabbaniah in 1990. All these banks were established in Bandung, West Java (Sumitro, 1996). Then, it was followed by the establishment of new Islamic banks, especially after the monetary crisis that occurred in 1998.

In Indonesia long before Bank Muamalat was established, there was similar bank-like business transaction, namely a cooperative. It was first introduced by Patih R. Aria Wiriatmadja in Central Java in 1896. He established a bank for government official staffs. This cooperative was based on profit sharing on their net income; this was actually implemented in Islamic laws. In addition, Islamic Trader Union (Serikat Dagang Islam) was founded in 1927, its aim was to strengthen local entrepreneurs to bargain and to develop in business. This organization also promoted profit sharing.4 After the colonization period, Muslims in Indonesia lost their practices in business to avoid the usage of interest. This can be caused by the economic system that

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The Conversion Effects of Islamic Unit to Full Fledged System Islamic Banks in Indonesia

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attached interest on it. In addition, there was no example of bank that utilized interest-free system at that time.

After financial reform known as June Package in 1983 and October Package in 1988 in Indonesia, there were many new banks established. The number of banks increased from 40 before 1988 to 240 banks in 1994 (Enoch et al., 2001), this included Bank Muamalat as the only Islamic bank at that time. This bank was established without specified Act for Islamic bank; it was not so popular at that time. Then Act No. 10/1998 was issued, this Act regulated banks to have Islamic activities in units or full fledged system. This Act superseded Act No 7/1992 which did not cover Islamic bank activities, it was only permitted profit sharing scheme. While, Indonesian Bank regulation No.8/3/PBI/2006 on 30 January 2006 permitted Islamic unit under conventional banks to open counter in their branch office. Finally, special Act for Islamic bank issued Act No. 21/2008. This Act still permitted to have Islamic units before converted to a full fledged Islamic banking system (Permana & Purba, 2008).

Bank Indonesia as the central bank seemed to be late in responding this phenomenon. They formed bureau which specialized in catering and observing Islamic banks in Mei 2001, then, they upgraded to directorate in August 2003 (Karim, nd). It was hoped that there is a higher legal and authority to support the development Islamic banks in Indonesia. So far there is no specific governor of central bank for Islamic banks in Indonesia.

The issuance of sukuk in 2008 can be supportive tools for Islamic banks to invest or as their money market instrument besides Indonesia Bank Certificate (SBI syariah). SBI syariah was issued after the Sertifikat Wadiah Bank Indonesia (SWBI) which did not offer competitive return, it was merely based on bonus. SWBI was supervised under Shariah Supervisory Board opinion No. 01/DSN-MUI/IV/2000 on current account. As SWBI was not so attractive, SBI syariah was launched in 2008, but it was prohibited to sell in the secondary market and regulated by Indonesian Bank regulation No. 10/11/PBI/2008 on SBI syariah.5

At last, the controversial issues in Islamic banks in Indonesia could be finalized, then there will be no more tax on value added (VAT). This is based on Act No. 42/2009 on VAT. Before, this can be a serious problem for Islamic banks as their main activities were in murabahah (selling activities). Some Islamic banks got sue and fines (BNI Syariah was penalized to pay Rp 393 billion6, and other Islamic banks as well) by Taxation Department as they did not pay the VAT which should no need to pay as it was similar to lending activities in the conventional banks.

RESEARCH METHODOLOGY

There were 28 Islamic banks under Islamic units until October 2008, then Lippobank merged into Bank Niaga and Bank Rakyat Indonesia (BRI) established into full fledged Islamic banking

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system followed by Bank Bukopin in November 2008. Thus, there were only two Islamic banks that converted to full fledged Islamic banks, namely Bank Rakyat Indonesia (BRI) and Bukopin at the beginning.

Table 1: Research Object

Information Number

Number Islamic Banks under Islamic units

28

Merged to other bank 1

Total 27

Not yet converted 25

Total observed 2

Source: www.bi.go.id

Islamic Banking Statistics in February 2010 stated that there were additional Islamic banks under full fledged system, they were Bank Panin Syariah and Bank Victoria Syariah. These banks established full fledged system without initially opening Islamic unit, then it was followed by others until there are 11 full fledged Islamic banks in Indonesia. Data was collected from Bank Indonesia, which provided biannual data, monthly Islamic banking statistics and Yahoo finance for the stock price. As it compared the data before and after conversion, event study would be the best analysis to provide better information. In addition, graph analysis and especially Wilcoxon test were conducted to see whether there is a significant difference before or after the conversion or otherwise.

ANALYSIS

The effects of conversion from Islamic units to full fledged system covered on the analysis of the financial position (including total assets, net income and deposits), benchmarking on stock price movement. Wilcox on test is to see the significance of the conversion statistically. From figure 1, we can see that in 2005 BRI Syariah had a bigger size compared to Bukopin Syairah in 2005. BRI Syariah increased significantly until its total asset became 3.5 fold in 2009 compared to that in 2005, while Bukopin Syariah was only 2.5 fold. The significant increase of BRI Syariah was after the conversion to full fledged system (see figure 1). BRI as the conventional bank acquired Bank Jasa Artha in 16 October 2009 then set it up for BRI Syariah


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(not shown in the graph). They acquired Bank Jasa Artha for Rp 61 billion.7 Until mid of 2011, it is 4 fold of BRI Syariah asset compared to Bukopin Syariah.

Figure 1. Total Assets of Converted Banks (in Rp million, June.

Source: Bank Indonesia

Consistent to the asset growth, BRI Syariah also enjoyed a significant net income in 2009, and remained steady until June 2010. On the other hand, Bukopin Syariah made a substantial loss in 2009. This loss was after the conversion process due to bigger operational expense of a new branch (see figure 4). However, at mid of 2011 they almost have a similar amount in net income. With very bigger asset, BRI Syariah should have bigger net income, this means the bank may not be optimum in generating profit.

Figure 2. Net Income of Converted Banks (in Rp million, June)


After the conversion, both banks suffered lower deposits. Especially Bukopin Syariah in which the deposit growth did not increase significantly before. This decreasing deposit can be a serious problem. On the other hand, BRI Syariah which had a significant increase before, the decreasing deposit may not be a big problem. This phenomenon can be an enthralling finding to be

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discussed further, why after the conversion can cause decreasing deposits. However, BRI Syariah enjoyed a very big significant increase in deposit amount after the acquisition (almost 5 fold in one year). The bigger is the total asset, the bigger amount of deposits. This means Islamic bank grew organically without other significant external funding.

Figure 3:Deposits of Converted Banks (in Rp million, June)


During Islamic unit scheme, these banks did not increase in term of branches. However, after the conversion, their branches decreased significantly especially for BRI Syariah. After that they can add new branches. In fact, Bukopin Syariah opened new branches in a quite aggressive way (see figure 4).

Figure 4:Number of Branches of Converted Banks


The analysis of the conversion effect to stock price movement may be misleading due to in bearish period. It can be seen that Jakarta Composite Index (JCI) also experienced the worst condition. In fact, Bank Rakyat Indonesia (BBRI) always at the top of JCI performance compared to Bukopin (BBKP (see figure 5). After the acquisition, only Bukopin’s stock price


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decreased. This may be caused that they acquired bank that was still under control and observation from Bank Indonesia. Bank Bukopin paid Rp 94 billion to acquire Bank Persyarikatan Indonesia to convert to be an Islamic bank. It was actually a bill of debt.8

Figure 5: Stock Price Movement of Converted Banks


To prove the significance of conversion from Islamic unit to full fledge system, we can utilize statistical test. As the data is not enough to cover the normal test, nonparametric test was conducted (see table 2). Wilcoxon test is a statistical test that can be used to check whether after the effect of one activity may have a significant effect or otherwise. We tested total assets, amount of net income and deposits to see the significant effect after the conversion. The results are that not all of those parameters have significant effects, especially for the net income. This test conducted the condition before and after six months of the conversion.

Table 2: Non-Parametric (Wilcoxon) Test

Item Total Asset

Net Income

Deposit

Z -1.342 -0.447 -1.342

Sig 0.18 0.655 0.18

Source: data

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0.2

0.4

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0.8

1

1.2

1.4

1.6

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Jun-

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Aug-

08

Oct

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Feb-

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Apr-0

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Jun-

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Aug-

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Dec-

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Feb-

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BRI Bukopin Acquisition


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However, currently there is another conversion from Islamic unit to full fledge Islamic bank, namely Bank Negara Indonesia Syariah in March 2010 and Bank Jabar dan Banten Syariah in January 2010. Other new full fledged Islamic banks were Bank Panin Syariah, Bank Victoria Syariah, Bank Central Asia Syariah, and Maybank Indonesia Syariah. These three banks directly open for full fledged Islamic banks.

CONCLUSION

Even though, the spin off process did not show a significant result statistically. This could become a trigger for other conventional banks to follow the conversion process. However, some conventional banks are still willing to set up full fledged Islamic banking system, they are Bank Panin, Bank Victoria, Bank Central Asia (BCA Syariah) and Maybank Indonesia Syariah directly. Another Islamic bank converted from Islamic units to full fledged system was Bank Negara Indonesia Syariah (BNI Syariah) and Bank Jabar dan Banten Syariah. If we see from the above figures, there is a promising prospect for Islamic banks which undergo the Islamic full fledged system. This may be caused by the flexibility for a bank to have its own strategy to grow faster such as issuing sukuk, or perhaps listing their stock in the stock market. In the short term period, the effects of conversion may not show significant results. It is hoped that the other 24 Islamic unit banks also follow the conversion process.

REFERENCES

Act No. 10/1998 on Banking.

Act No. 21/2008 on Islami Banking.

Antara. (2007). BRI Akuisisi Bank Jasa Arta Rp 61 Miliar. At http://www.antara.co.id/print/1183364004.

Bank Indonesia. (2005). Islamic Banking Statistics in June 2005.

Bank Indonesia. (2005). Islamic Banking Statistics in December 2005.






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Bank Indonesia. (2012). Islamic Banking Statistics in April 2012.

Bank Indonesia. At www.bi.go.id.

Bataviase. (2010). Bank Syariah Desak Penghapusan Pajak. At http://bataviase.co.id/node/81828

Enoch, Charles, Barbara Baldwin, Olivier Frecaut, & Arto Kovanen. (2001). Indonesia: Anatomy of a banking crisis teo years of living dangerously 1997-1999. IMF Working Paper.

Karim, Adiwarman. nd. Prospek dan Tantangan Ekonomi Syariah di Indonesia .

Ministry of Cooperative, Small and Medium Enterprises. At http://www.depkop.go.id/

Nunun. (2007). Bukopin Beli Aset Kredit BPI. At http://www.suarakarya-online.com/news.html?id=179270.

Permana, A.R & Purba A. (2008). Sekilas Ulasan UU Perbankan Syariah. Buletin Hukum Perbankan dan Kebanksentralan 6 (2).

Sumitro, Warkum. (1996). Asas-Asas Perbankan Islam dan Lembaga-Lembaga Terkait. Jakarta: Raja Grafindo Persada.

Vibiznews. (2008). Sertifikat Bank Indonesia Syariah : Terobosan Baru Perbankan Syariah At http://vibiznews.com/articles_financial.php?id=74&page=syariah.


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