Driven determinants to indonesia sharia commercial banks' performance: The important role of diversification strategy

Nội dung text: Driven determinants to indonesia sharia commercial banks' performance: The important role of diversification strategy

1. DRIVEN DETERMINANTS TO INDONESIA SHARIA COMMERCIAL BANKS' PERFORMANCE: THE IMPORTANT ROLE OF DIVERSIFICATION STRATEGY Sobar M Johari1 – Ammelia Rizza Fitri Ayu L.C2 – Nguyen Tran Thai Ha3 Abstract: This study aims to analyze the role of income diversification and asset diversification on the sensitivity of the determinant of the Net Operating Margin (NOM) of Islamic Commercial Banks (ICB) in Indonesia. By using endogenous switching regression analysis techniques, the researcher assumes that the influence of the NOM’s determinant can be different when the bank has high diversification and low diversification. By dividing the two regimes on the diversification variable, the researcher can determine which regime the NOM will be more sensitive to the fluctuation of the NOM’s determinant. The results of this study indicate that operational costs have an essential role in determining the level of NOM. NOM tends to be more sensitive to the its determinants when the ICB is not functionally diversified compared to ICB, which diversifies its income and assets. This study also found that a large ICB has a greater probability of diversifying high income than a small ICB. Keywords: Net Operating Margin, Diversification, Islamic Commercial Banks, Endogenous Switching Regression. 1. INTRODUCTION Net operating margin (NOM) is a financial performance measure of profitability in Islamic banks (ICB). NOM is a ratio that represents the ICB’s ability to create profit by considering the difference between the revenues generated from financing activities and costs incurred in raising activity. Banking margins are often linked by the level of banking efficiency, especially in Indonesia, which is a developing country. Higher Spread usually an indication that banks are economically inefficient in performing intermediation activities in mobilizing the resources that can be invested (Demirguc–Kunt, Asli et al., 2004). Conversely, lower spread reflects the efficiency of intermediation costs and the effectiveness of the monetary policy. As the importance of the banking margin level, some previous researchers have attempted to determine and analyze the characteristics that can describe the level of a bank's margin. Ho and Saunders (1981) was the first researcher to develop a model dealership to determine the determinant of a conventional bank margin in the United States. Researchers have also carried out the expansion of the model of Ho and Saunders (1981) thereafter to include other factors which may reflect the level of bank margins such as Maudos and Fernỏndez de Guevara (2004) and Carbú Valverde and Rodrớguez Fernỏndez (2007) such models are generally analyzed on conventional banks whose operations are based on interest. However, the determinant margin of the banking institutions may have different effects when applied in the context of Islamic banking operations do not rely on the flowers. Thus, the issues relating to how the net operating margin in ICB in Indonesia optimally determined and how their sensitivity to changes in the banking environment need to be studied further. 1 Department of Business Administration, Asia University, Taiwan. Department Syariah Economics, Universitas Muhammadiyah Yogyakarta (UMY), Indonesia. Email: sobarjohari83@gmail.com. 2 Department of Economics, Universitas Gadjah Mada (UGM), Yogyakarta, Indonesia. Email: ammeliarf@gmail.com. 3 Faculty of Finance and Accounting, Saigon University, Vietnam. Email: thaihasgu@gmail.com. 568
2. Islamic banks in Indonesia is a unique object for study, especially at the level of its margin. Some previous researchers revealed that the overall margin rate banking institutions in Indonesia are relatively high compared with other countries such as in Asia, East Asia, and ASEAN in which the average margin of banks in Indonesia are in the top four per cent (Lin et al., 2012; Lúpez–Espinosa et al., 2011). Some of the previous investigators discovered overpricing their behaviour in an Islamic commercial bank that operates with a higher margin level compared to conventional banks (Shaban et al., 2014; Olson and Zoubi, 2008). The importance of maintaining the level of bank margins as well as the nature of the revenues in traditional activities (main) cyclical, in which the nature of the revenues in traditional activities depend on the strength of customer demand and changes in the economic cycle (Lin et al., 2012), causing some of the banking industry in the various country pursuing a strategy of diversification of financial products is no exception to the ICB in Indonesia (Abedifar et al., 2013; Birchwood et al., 2017). This diversification strategy can be done either through the diversification of their assets such as channel financing to various other types of contracts, and other financial services' potential income are a variety of ways, including diversifying revenues in non–traditional activities such as revenue services (fee) as well as commission revenue. Diversification of activities is expected to reduce their dependence on traditional activities, face the level of competition, increase market share and reduce the risk. Some previous researchers have studied the benefits of diversification, but the results of empirical research tend to be varied and inconclusive. According to the hypothesis conglomerate, diversification activities can add value because they can provide one–stop shopping to consumers willing to pay more to increase their income (Berger et al., 2000). On the other hand, according to the hypothesis focused strategy, financial institutions should focus on a single business line to take the greatest advantage of the expertise of management and reduces the agency problems (Jensen, 1986; Denis et al., 1999). Variations in previous studies to assess the benefits of diversifying, and the lack of literature review discusses the benefits of diversification against NOM determinant of sensitivity to the IB; therefore, this study aims to analyze the role of income diversification and asset diversification sensitivity NOM determinant in Indonesia period 2010– 2017. Using endogenous switching regression analysis techniques, the researchers assume that the determinant influence on the NOM may be different when the bank diversified into high and low diversification. By dividing the two regimes on diversification variables, researchers can determine at what NOM regime will be more sensitive to the fluctuations of its determinants. These results indicate that operating costs have an important role in determining the level of NOM. NOM tends to be more sensitive to its determinants when ICB is not functionally diversified than ICB diversify income and assets. The study also found that a large ICB has a greater probability of diversifying revenue higher than small ones. A review of the prior literature is presented in Section 2, followed in Section 3 by a description of the dataset and an explanation of the methodology adopted for this study. Our empirical results are presented in Section 4. Finally, the conclusions drawn from this study are presented in Section 5. 2. LITERATURE REVIEW 2.1. Effect of financing risk to net operating margin Financing risks are the potential losses faced by banks when the debtor does not fulfil its obligation to return the capital, and the handed portion of profits has been agreed. In practice, there is always a trade–off in assessing the risks and returns. Banks always want to adjust prices based financing of customer financing risk financing (Lepetit et al., 2008). The higher the risk, the greater the bank returns expected from the finance portfolio (risk–return trade–off). As a result of these risks can increase 569
3. margins through pricing Islamic bank financing higher. Fungỏčovỏ and Poghosyan (2011) found a negative relationship between risk and margin financing banks in Australia, Kenya and Russia when using a non–performing loan (NPL) as a proxy that is different from previous studies. They found a negative relationship can be explained by using the argument to the Russian market discipline (Karas et al., 2013). Based on that argument, depositors require higher premiums to deposit their savings in banks are riskier, for example, to banks with bad loans ratio higher. The increase in deposit rates will ceteris paribus contribute to the decline in interest margins, thereby establishing a negative relationship between problem loans and margin. H1: Risk financing negatively affect the net operating margin 2.2. Effect of liquidity risk to net operating margin Liquidity for the bank includes two things, namely the ability of Islamic banks to meet maturing liabilities and the ability of Islamic banks to obtain cheap funds. From two such coverage, it can be ascertained that the bank's asset portfolio is dominated by illiquid assets. The main composition of bank assets is the entire financing extended to the majority of debtors whose term of more than one year. On the other hand, the majority of which is owned bank liabilities derived from third party funds which all deposits with a term of less than one year. Therefore mismatch (mismatch) on aspects of the time period, the bank will easily be exposed to liquidity risk. Ascarya and Yumanita (2010) found a positive and significant relationship between liquidity risk and the margin of banks in Indonesia in 2006–2009. Liquidity risk can positively related to bank margins because when more liquid assets owned by the bank compared with its obligations, the higher the level of the bank's margin. According to them, the reason behind this positive correlation is based on the commercial banking market structure in Indonesia tend to be concentrated. Moreover, Brock and Rojas Suarez (2000) found that the liquidity risk is measured using the loan to deposits ratio was positively related to bank margin, it is based on the argument that the greater the LDR owned banks, characterizing that the bank has a high intermediation ratio in channel financing to the public. This will trigger increased bank margins because of revenues from the distribution of funding likely to be higher than the cost of raising funds. According to Birchwood et al. (2017) LDR can have a positive tie to the margins. Islamic bank liquidity risk is measured using the financing to deposit ratio (FDR) is an intermediation ratio which reflects the ability of Islamic banks in channelling funds to the community. The higher the ratio, the higher FDR banking liquidity risk, however, will be whether banks in disbursing financing and earn income from financing activities. Through the perspective of economies of scale, the greater the distribution of funding then there are efficiency benefits arising from the cost per unit for the management and distribution of the financing portfolio, which means that the bigger the bank channel financing of the revenue from the activity of the finance portfolio will be greater than the costs incurred from the activity of collection, causing the bank's net operating margin to be increased (Fungỏčovỏ and Poghosyan, 2011). H2: Risk Liquidity positive effect on net operating margin. 2.3. Effect of third party funds market share to net operating margin The paradigm of market forces stated that the increase in market forces would lead to gains and benefits to monopolize the market, which it will lead to increased levels of a bank's margin. Hypothesis structure–conduct–performance revealed that the banks in a concentrated market tend to collude in setting their interest margins and thus can improve the net interest margin (Naceur and Omran, 2011). So also with the larger banks can use their market power in pricing and pay a lower rate for depositors, so get a higher margin. Market power held by banks may also be reflected in the market share of 570
4. banking, and this is supported by several empirical studies that measure the strength of a bank in the market using market share as Lee and Isa (2017), and Perera et al. (2010). A cross–country study by Demirguc–Kunt, A. and Huizinga (1999) found that banks with a market share a greater positive impact on the interest margin so as to increase their margins. H3: Third party fund market share positive effect on net operating margin 2.4. Effect of operating costs to net operating margin The concept of operational costs capable of affecting the margin of banks led by Maudos and Fernỏndez de Guevara (2004). They developed the main model of Ho and Saunders (1981) by adding variable operating costs as a critique of their model that the model fails to consider the bank as a company with production function related to intermediation services, such as administrative fees for maintaining the loan or contract deposits. Maudos and Fernỏndez de Guevara (2004) responded to this criticism and extend their model by adding the operational costs of production functions to capture bank–related bank services. Also, they consider the bank's operational costs as a determinant of banking margins. They found, in essence, even in the absence of market power and all types of risks, the banks had to close their operating costs, which is a function of the deposits taken and loans. Therefore, banks operating at a level higher costs have to charge a higher margin. They found a positive relationship between bank margins and operating costs in the European banking sector. Therefore, banks operating at a level higher costs have to charge a higher margin. H4: Operating costs have a positive effect on the operating margin 2.5. Effect of capital to net operating margin The level of capital in this study was measured using the ratio of equity to total assets. The ratio of equity to total assets measures how much capital banks are used to fund the entire assets of the company. The higher the ratio of equity to total assets reflect the higher the equity to assets ratio, the less leverage, meaning that a greater percentage of assets owned by the company and its investors. If the source of the equity funds is more expensive than on external funding sources, banks will tend to assign a high margin to fund their equity. The relationship between capital and Islamic banking margins disclosed by empirical research in various countries. Brock and Rojas Suarez (2000) argued that the banks that have a capitalization bad (risky) might have an incentive to lower interest rates on loans and raising interest rates on deposits to obtain a market share larger so that the level of capital can have a positive relationship to the margins. Additionally, Gambacorta and Shin (2018) found that a high ratio of equity to total assets associated with a lower cost of raising funds in developed countries, where the cost benefits that were priced at the margin, then the relationship between equity to total assets and margins can be negative. H5: Capital positive effect on net operating margin 2.6. Effect of diversification to the financing risk, liquidity risk and net operating margin Islamic banks, in contrast to a conventional commercial bank where Islamic banks must abide by Sharia laws so that the benefits of diversification should have been more pronounced in the Islamic banks because of their features of the division of risk (risk sharing) ensure mitigation of any increased risks associated with diversification. Non–exploitative nature (prohibition of interest–based loans) of Islamic banking ensures fairness between the different stakeholders so that the agency problem resulting from diversification should be minimized in Islamic banks (Magalhóes and Al‐Saad, 2013). Additionally, Islamic banks are usually less diversified than a conventional bank (Chatti et al., 2013). Moudud–Ul–Huq et al. (2018) analyzed the impact of diversification of income and assets to the 571
5. performance and risks of banks in ASEAN countries in 2011–2015 found that income diversification on banks in Indonesia can be more profitable because it can improve performance and reduce risk. The results are consistent with the results of Chen et al. (2018) which suggests that the diversification of assets play a role in the performance of Islamic banks in Indonesia, Malaysia and Pakistan in 2006 to 2012. They found that diversification of assets had a positive effect on the profitability and efficiency of Islamic banking. In measuring the effects of diversification income, Gamra and Plihon (2010) found a non–linear relationship exists between diversification, risk and performance of the 714 banks in East Asia and Latin America. H6: risk sensitivity of the net operating margin financing differ between Islamic banks that have a high level of revenue diversification, and diversification of assets is high. H7: liquidity risk sensitivity of the net operating margin differ among Islamic banks that have a high level of revenue diversification and diversification of assets is high. 2.7. Effect of diversification to the third party funds market share and net operating margin Relative Theory of Market Power (RMP) stressed that only companies that have a large market share and differentiated product that is able to use market forces and profit above normal (Shepherd, 1986). In the theory of market’s power is one reason the company to diversify is to increase market share. Therefore, banks are diversifying expected to have a large market share so that they can use the market power to set interest rates low savings and high–interest rate loan so as to increase the margin of the bank. The research result Nguyen (2012), which examines the relationship between market power and revenue diversification, they found a non–linear relationship between the bank and the market power of banks to diversify their income in ASEAN. At a low degree of market power in the market of loans and deposits, the bank manager tends to find and take advantage of new growth opportunities in non–traditional markets, leading to higher revenues from non–traditional activities. On the other hand, banks with greater market power in the market of loans and deposits, they are more focused on traditional interest–based products (net interest income). H8: the sensitivity of third party fund market share against net operating margins is different between Islamic commercial bank that has a low level of income diversification, and asset diversification is low. 2.8. Effect of diversification, operating expenses and net operating margin One reason for the bank to diversify due to potential cross–selling to increase the scope of the banking economy (Elsas et al., 2010). The existence of the conditions under which the bank has a long– term relationship with their clients can benefit banks by collecting extensive information about customers and use this information again, not only in the business areas in which the information was originally collected but also in areas unrelated business. Banks are diversifying in related businesses can take them to benefit costs and gain a broader economic sphere. Gertner and Scharfstein (1991) argued that the internal capital markets increase the incentive to do the monitoring. Although monitoring the diversified company can improve operational performance, but it can also increase operating costs significantly. These results can be interpreted that at the level of lower revenue diversification, banks can benefit from the economic sphere (economies of scope) and bring the cost per unit lower. However, efficiency gains decreased at a rate of excessive diversification. This suggests that excessive diversification into non–traditional activities do not improve efficiency. Based on these, H9: the sensitivity of operating expenses to net operating margin was not different between Islamic banks that have a high level of revenue diversification and a high asset diversification 572
6. 2.9. Effect of diversification to capital and net operating margin Banks use debt financing for most of them, in which the equity capital serves as a buffer to absorb losses and reduce the likelihood of financial difficulties. The higher equity than its total assets reflects a greater percentage of assets owned by the company and its investors that banks have the ability to absorption greater risk and can increase public confidence. On the other hand, the higher the bank's equity reflects the fewer resources other than equity funds in bank assets such as Third Party Fund (DPK), liabilities to other banks, issuance of securities, and so on, thus reducing the probability of banks to create profit. More diversified banks that have a relatively greater need for equity capital, especially if diversification involves expansion into sectors in which the bank is less effective to manage it (Winton, 1999). However, the bank with a high level of the capital market has a large probability of diversifying both the asset and the earnings (Karakaya and Er, 2012). Meanwhile, according to DeYoung and Roland (2001) found that banks with non–traditional sources of income that can increase earnings volatility. Large banks are more involved in the derivatives market and have a great degree of asset diversification tend to have lower capital ratios, thus lowering the probability of banks to increase margins high. Based on this, the researchers suspect that the NOM sensitivity of capital to be different when the ICB to diversify income and asset diversification. H10: The sensitivity of capital to net operating margins is different between the Sharia Islamic commercial bank that has a high level of revenue diversification and a high asset diversification 3. RESEARCH FRAMEWORK, DATA AND METHODOLOGY 3.1. Research framework Figure 1. Research framework Financing risk Liquidity risk Net operating margin of Diversification strategy bank Third party funds market share Operating costs Operating costs 3.2. Data This study used a sample of the Islamic Banks in Indonesia, which is already up and spin–off in 2010 and published financial statements since the first quarter of 2010 to the fourth quarter of 2017. The data used in the form of financial ratios panel data published by the financial services authority 573
7. period 2010– 2017. Our final dataset panel was comprised of 10 banks, providing a total of 320 bank– year observations. Table 1 reports the median and means values of the bank variables, while Table 3 depicts the Pearson correlation coefficients of all of the variables used in this study. We extended the models of Lin et al. (2012), utilizing a switching model of net operating margins in an attempt to determine the importance of bank diversification; the models were based on the Hu and Schiantarelli (1998) endogenous switching regression models. Depending on the switching function, the net interest margin equation can be in either of two regimes, both of them which are unobserved by the researcher, and Characterized by different values of the coefficients of the bank–specific control variables. The estimation of the switching function Allows us to assess the statistical and economic significance of the characteristics of the different banks in Determining the probability of being in one of two regimes: a 'high degree of diversification' (hd) or a 'low degree of diversification '(ld). The basic specification of the switching models of net interest margins is defined as follows, with the net operating margin equation for bank i, operating in a low degree of diversification regimes, at time t, being: NOMit = αo + β₁NPFit + εit (1) NOMit = αo + β₂FDRit + εit (2) NOMit = αo + β₃MSit + εit (3) NOMit = αo + β₄BOit + εit (4) NOMit = αo + β₅EQTAit + εit (5) NOMit = αo + β₁NPFit + β₂퐹 푅it + β₃ 푆it + β₄ it + β₅ 푄 it + εit (6) and Iit = 1 if γZit + Uit > 0 Iit = 0 if γZit + Uit ≤ 0 we have: X βᴸᴰ + ε₁, if Z γ + u ≤ 0 it it it it NOMit = ( (7) X βᴴᴰ + ε₂, if Z γ + u > 0 it it it it Model (1) to (6) aims to answer the first research question by using seemingly unrelated regression analysis techniques, while the (7) model of the research aims to answer the second question by using an endogenous switching regression analysis techniques. Where NOM is the net operating margin; NPF is non–performing finance as a proxy of risk financing; FDR is financing to deposit ratio as a proxy of liquidity risk; MS is the market share; BO is the operating costs; ETA is equity to total assets as a proxy of capital. The Zit vector in each of the specifications of the switching function represents a set of diversification variables, comprised of the ratio of non–financing income to total operating income (NFI), the loans–to–assets ratio (LTA). Followed by Baele et al. (2007) to adopt a pragmatic definition of the degree of functional diversification for our empirical analysis, relying on one asset–based measure and one broad measure of the relative diversification, both of them which are publicly available and widely used by analysts and investors to assess the long–term potential and risk of banks. Any bank with a lower loans–to– assets ratio or a higher proportion of non–interest revenue was regarded as being more oriented towards non–traditional banking activities. An alternative approach is to follow Baele et al. (2007) and Laeven and Levine (2007) to construct measures of asset and revenue diversity; asset diversity is based on the stock variables, while revenue diversity is based on the flow variables, with these diversity measures defined as follows: Diversity = 1– |2x – 1|, Where x is either the loans–to–assets ratio or the ratio of non–interest income to total operating income. The diversity 574
8. variables, which take values between 1 and 0, with an increase of the degree of diversification. Based Hu and Schiantarelli (1998) model of endogenous switching regression assumes that the function of net operating margin and switching functions, vector error terms (ε₁it, ε₂it, uit) normally distributed and independent with an average equal to zero and covariance matrix 1 equal to Σ, where (ε₁it, ε₂it, uit) ~ N (0, Σ), Σ = NOM function is the probability of occurrence of each regime as follows: LD Prob (=) MitNOM it = Prob (Zitγ + uit < 0) = Prob (uit < – Zitγ) = Φ (–Zitγ) LD Prob (=) MitNOM it = Prob (Zitγ + uit 0) = Prob ( uit – Zitγ) = 1 – Φ (–Zitγ) 4. RESULTS AND DISCUSSION Table 1. Descriptive statistics Variables Bank mean median BCA BJB BNIS BRIS BSM BUK MEGA MUA PANIN VIC 푖푡 2.98 3.11 3.95 3.90 3.27 1.79 6.44 2.22 2.49 2.02 3.21 2.66 푃퐹푖푡 0.29 2.83 1.66 2.97 2.47 3.11 2.29 2.95 1.12 2.98 2.27 1.94 퐹 푅푖푡 86.54 102.46 91.24 94.43 88.20 69.09 92.01 95.36 108.56 74.28 90.22 91.41 푖푡 5.61 7.66 4.28 4.93 5.80 4.94 9.79 4.26 3.98 4.98 5.62 4.80 푖푡 23.98 16.45 11.47 10.01 7.39 9.86 11.76 6.91 25.90 20.01 13.7 11.38 푆푖푡 0.90 2.52 9.94 10.20 3.36 3.77 4.28 26.84 2.13 0.55 6.44 4.26 푖푡 41.55 54.80 59.32 41.00 41.66 43.94 41.93 43.93 57.94 65.50 49.15 49.54 푅 푖푡 34.00 23.66 32.74 23.69 51.13 51.45 44.14 38.75 24.63 54.59 37.87 32.34 퐿 푖푡 77.52 72.30 70.30 79.49 79.16 78.02 79.03 78.03 67.65 58.69 74.01 75.11 퐹 푖푡 17.74 16.00 16.37 11.84 26.22 27.74 25.07 19.37 12.31 29.76 20.25 16.17 푆푖 푒푖푡 14.60 15.26 16.48 16.55 17.84 15.22 15.63 17.54 14.82 13.74 15.77 15.67 Source: authors The average value of the dependent variables, independent and diversified consisting of net operating margin (NOM), financing risks (NPF), liquidity risk (FDR), operational cost (Bota), Capital (EQTA), market share (MS); diversification variables were measured using income diversification (Rd), diversification of assets (Ad) variables were measured using the instrument for the diversification of the loan to total assets (LTA), non–financing income to operating income (NFI). Diversification of assets and income are measured using the formula 1– | 2x–1 |, where x is the loan to total assets and non–financing income to total operating income. 575
9. Table 2. Correlation matrix 푖푡 푃퐹푖푡 퐹 푅푖푡 푖푡 푖푡 푆푖푡 푖푡 푃퐹푖푡 –0066 퐹 푅푖푡 0054 –0.0893 푖푡 0591 0.0544 –0015 푖푡 –0.1310 –0.4724 0.0727 –0.0509 푆푖푡 –0.0064 0.1508 0.0172 –0.0775 –0.4761 푖푡 0.0044 –0.0741 –0.0942 –0.0243 0.0012 0.0062 푅 푖푡 –0.1969 0.1182 –0.2401 0.1289 –0.0965 0.1693 0.0920 Source: authors Table 3. Cross–sectional regression using sur Variables Model (1) Model (2) Model (3) Model (4) Model (5) Model (6) 3.23 3.21 2.58 3.23 3.22 3.23 Constant (26.02) (25.33) (20.16) (25.91) (25.99) (26.02) –0,004 –0.01 푃퐹푖푡 (–0.74) (–0.82) 3.39 8.14 퐹 푅푖푡 (0.10) (0.16) 11.71 12.02 푖푡 (8.38) (8.45) –0.11 –0.19 푖푡 (–0.72) (–0.79) –0.00 –0,007 푆푖푡 (–0.01) (–0.03) 2 0.0005 0.0003 0.2100 0.0010 0.0000 0.0210 Source: authors Significant at alpha 5%, Significant at alpha 1% and () is t–statistic The regression analysis using the SUR can be seen in Table 3 model of one to six who explained that the only variable operating costs are proxies by the ratio of operating expense to total assets that are detrimental to reflect the net operating margin sharia banks in Indonesia in the period 2010–2017, the fourth hypothesis in this research is supported. The results of this study indicate that there is a positive relationship between operating costs and NOM, means higher operating costs that are owned by the higher–level ICB NOM. The results of this study indicate that the ICB in Indonesia in setting the level of the margin depends on the level of efficiency of operations, where high operational costs reflect the low level of efficiency ICB. This is in line with the opinions Maudos and Fernỏndez de Guevara (2004), which uses a multi–output framework in establishing a logical connection between the operational costs of the margin of the banking institutions. Their result confirms that the absence of market forces and all types of risks, the banks had to close their operational costs, which is a function of the operating costs of funds raised and the financing provided by the banks. 576
10. Based on published reports of financial ICB, operating costs are high on the ICB during the study period due to the decline in asset quality, so ICB need to prepare Allowance for Impairment Losses (CKPN) larger (SPS, 2017) because of the increase in operating costs will trigger NOM increase ICB. Besides, the quantity and quality of human resources (HR) is inadequate and information technology (IT) that has not been able to support the development of financial products and services to be triggered ICB in Indonesia have high labour costs. This can be an obstacle for considering ICB in Indonesia is a new industry and is still in the growth stage, so as to meet the quality and capacity of human resources and IT is becoming a challenge for the ICB to understand and implement in accordance with Islamic principles. Therefore, not yet adopted the inability ICB reliable IT systems, ICB requires several branch offices in order to facilitate and improve access to, and use of Islamic financial products to the general public and thus require more labour, and is followed by an increase in operating costs. 4.2. Endogenous switching regression result Table 4. Estimation results endogenous switching regression when islamic banks perform diversified income Net Operating Margin function Variables Switching Function Low degree of High degree of diversification diversification Coeff. t–statistic Coeff. t–statistic Coeff. t–statistic Constant .3838487 0.57 2.21848 2.54 0.13423 0.33 푃퐹푖푡 –.13499 –1.47 –.21078 –2.46 – – 퐹 푅푖푡 –.007153 –1.10 .007499 1.16 – – 푖푡 .504749 12.15 0.2393 8.67 – – 푖푡 –.011621 –0.59 –0.0313 –1.44 – – 푆푖푡 .0339191 2.47 –0.0002 –0.02 – – 퐹 푖푡 .3838487 0.57 2.21848 2.54 0.1506 2.35 퐿 푖푡 –.13499 –1.47 –.21078 –2.46 –0.0043 –0.83 Log likelihood. –763.30132 LR test. 20.50 Total no. of observation. 320 Source: authors Significant at alpha 5%, Significant at alpha 1% 577
11. Table 5. Estimation results from endogenous switching regression when islamic banks perform diversified assets Net Operating Margin function Variables Low degree of High degree of Switching Function diversification diversification Coeff. t–statistic Coeff. t–statistic Coeff. t–statistic Constant 2165 2.28 1,528 2.05 7,083 8.94 푃퐹푖푡 –0.2818 –2.64 –0.1232 –1.17 – – 퐹 푅푖푡 0.00586 0.77 0.0023 0.37 – – 푖푡 0.42940 11.61 0.18937 6.07 – – 푖푡 –0.0624 –2.30 –0.0218 –1.09 – – 푆푖푡 –0.0090 –0.73 –0.0183 –1.56 – – 퐹 푖푡 0.1912 2.91 퐿 푖푡 –0.0953 –9.38 Log likelihood. –720.39252 LR test. 10.47 Total no. of observation. 320 Source: authors Significant at alpha 5%, Significant at alpha 1% 4.2.1. Effect of diversification on the sensitivity of risk financing and net operating margin In the regime of the high level of revenue diversification and asset, diversification is low, NPF coefficient as a proxy of the risk of financing has a significant negative coefficient on the NOM. The results support the hypothesis into six research that says that the NPF sensitivity towards different NOM when ICB diversified high income and high asset diversification. The results of this study can be interpreted that the NOM can be more sensitive to fluctuations in financial risk when ICB diversified high income and low asset diversification. Based on these results, there are some possible arguments that cause significant negative relationship NPF against NOM. First, the negative relationship between NPF and NOM occurs when the ICB to diversify the assets are low, meaning that when the assets of Islamic banks focused on the activities of the traditional is the distribution of funding (financing), NOM can be more susceptible to fluctuations of financing risk, thus increasing the ratio of NPF cause NOM decrease Islamic commercial bank. Based on Islamic banking statistics published by the FSA in 2010–2017 product distribution of financing Islamic banks in Indonesia is still dominated by the Murabaha contract where the product has NPF ratio is higher than other financial products. This is reflected in Islamic Banking Statistics (SPS) from 2010 to 2017, there was an increase of NPF ratio during 2014–2017 due to dominating the Islamic bank financing products based Murabaha contract. The concentration of Islamic commercial bank financing products (diversification of assets less) has a margin of Islamic banks more sensitive to fluctuations in financial risk that could potentially reduce the margin of Islamic banks. Second, the results of this study support the research of Carbú–Valverde et al. (2009), which revealed that banks that diversify high income tend to have low margin levels. This can also occur because of the cross–subsidization strategy. Banks that diversify high in income can get high income 578
12. from non–financing activities and hope to offer their traditional products with very small or even negative margins to maintain or attract customers given the market share of Islamic banks is still smaller than conventional banks. So, under conditions of high financing risk, Islamic commercial banks can provide a low margin level when diversifying high income. 4.2.2. Effects of diversification on the sensitivity of third party fund market share and net operating margin In a regime with a low level of income diversification, the market share coefficient of third party funds has a significantly positive coefficient on NOM. The results of this study support the eighth hypothesis of this study which states that the sensitivity of the market share of third–party funds to the NOM differs when ICB conducts low–income diversification and low asset diversification. The results of this study can be interpreted that NOM can be more sensitive to fluctuations in the market share of third–party funds when ICB diversifies into low income. Based on the results of these studies, there are several possible arguments that lead to positive and significant market share relationships with NOM, especially when banks make low–income diversification. First, the results of this study are in line with the market power theory that banks that have a high level of market share will have greater power to set high margins, only these results can only be confirmed at a low level of income diversification. According to Nguyen (2012) banks that have a larger market share both in financing distribution products and fund collection products, they will be more focused on traditional financial products than diversifying because they have been able to reap the benefits of their traditional activities. Second, the results of this study are in line with the results of the Trinugroho et al. (2018) who found that Islamic banks that have large market power are able to set high margins when diversifying is low. Islamic banks that focus on one type of financing contract such as Murabaha will be directly affected by market competition. This finding can relate to the fact that Islamic bank competitors also use Murabaha financing contracts because the contract is the most popular contract and has a lower level of risk than other contracts (Chong and Liu, 2009; Khan, 2010; Shaban et al., 2014) Therefore, the contract of Murabaha financing on the loan market is a very competitive contract, and Islamic banks need to set their margins to follow the competitive conditions that exist in the market, thus building a positive relationship between the two. 4.2.3. Effects of diversification on the sensitivity of operational costs and net operating margin Operational costs (BO) have a positive relationship to net operating margin both when the ICB is in a regime of high and low levels of asset and income diversification. The results of this study support the ninth hypothesis of this study which states that BO sensitivity to NOM does not differ between ICB, which diversifies high income and high asset diversification. Compared to other variables, operational costs have the greatest impact on ICB margins, according to Maudos and Fernỏndez de Guevara (2004) without market forces and all types of risks, banks must cover their operational costs which are a function of third party funds collected and channelled. Diversification activities, both high and low on and bank income tend to require costs and reduce the level of efficiency of Islamic banks. In addition, ICB operating at a higher level of operational costs reflects a low level of cost efficiency, so that ICB in its intermediation services is still constrained by more expensive cost structures; therefore ICB tends to price these operational costs into its margins. On the other hand, despite having a low level of efficiency, diversifying assets and high income can increase the margin like general sharia. This finding supports the results of Saunders and Walter (1994)'s research, which found a negative effect caused by diversification activities in the form of increasing unit costs along 579
13. with an increase in widespread activity. Diversification activities tend to increase ICB operational costs, so Islamic commercial banks operating at higher cost levels impose higher margins. 4.2.4. Effects of diversification on capital sensitivity and net operating margin Capital has a significant negative relationship to net operating margin when in a low asset diversification regime. The results of this study do not support the tenth hypothesis of this study which states that capital sensitivity to NOM is different when ICB diversifies high income and high asset diversification. This result can be interpreted that the lower the level of equity capital owned by ICB will trigger an increase in ICB margins or any increase in ICB capital, it will trigger a decrease in ICB margins, especially in the low level of asset diversification. There are several reasons that can explain the significant negative relationship between the two. First, the Financial Services Authority regulation No.11/POJK.03/2016 concerning the obligation to provide minimum capital for commercial banks in order to increase the absorption of risks caused by crisis conditions and/or excessive bank credit growth, Islamic banks must meet the ratio. In order to protect stakeholders and meet the minimum capital requirements by the government, Islamic banks will tend to hold back funds or channel funds to investments that tend to be safe, such as government securities based on sharia principles in order to minimize large losses. Therefore, the bank will experience a decrease in margin due to holding its funds and reducing lending to the community, thereby reducing the opportunity for ICB to obtain margin despite having a high level of capital. Table 6. Results of endogenous switching regression estimates when islamic commercial banks diversify income using bank size Net Operating Margin function Variables Low degree of High degree of Switching Function diversification diversification Coeff. t–statistic Coeff. t–statistic Coeff. t–statistic Constant 1.2758 0.7565 2.0966 2.44 4.1820 2.39 푃퐹푖푡 –0.3118 –3.08 –0.2489 –2.91 – – 퐹 푅푖푡 0.0020 0.30 0.0130 1.81 – – 푖푡 0.5155 10.51 0.2240 8.18 – – 푖푡 –0.0486 –2.56 –0.0357 –1.62 – – 푆푖푡 0.0257 1.40 –0.0089 –0.73 – – SIZE푖푡 0.2648 2.33 Log likelihood. –743.61LR test. 22.42 Total no. of observation. 320 Source. authors Significant at alpha 5%, Significant at alpha 1% 580
14. Table 7. Results of endogenous switching regression estimates when islamic commercial banks diversify assets using bank size Net Operating Margin function Variables Low degree of High degree of Switching Function diversification diversification Coeff. t–statistic Coeff. t–statistic Coeff. t–statistic Constant 2.18974 2.27 2.05994 2.46 8.58609 8.50 푃퐹푖푡 –0.2991 –2.91 –0.2842 –2.66 퐹 푅푖푡 0.0062 0.83 0.0003 0.06 푖푡 0.4330 11.76 0.25143 7.39 푖푡 –0.0662 –2.56 –0.4647 –2.24 푆푖푡 –0.0941 –0.76 –0.1615 –1.09 SIZE푖푡 –0.009 –0.23 Log likelihood. 711.831 LR test. 15.52 Total no. of observation. 320 Source. authors Significant at alpha 5%, Significant at alpha 1% Based on the size of the bank (size) on the switching function Tables 6 and 7 the coefficient on the variable size has a significant positive coefficient when the bank diversifies income and has a significant negative coefficient when the bank diversifies assets, but the sensitivity of the NOM determinant to NOM shows unchanged results. Therefore, every increase in the size ratio, Islamic commercial banks have a high probability of diversifying high income rather than diversifying high assets. This can occur because the average size of sharia commercial banks is still small and difficult to achieve a strong foothold in fee–based income–based activities. Another reason that could support this finding could be that small–sized Islamic commercial banks may only have more expertise in traditional activities but, have little expertise and experience in non– traditional activities (Laeven and Levine, 2007). In addition, small–sized ICB on average has low quality and capacity in HR and information technology systems, while diversifying non–traditional activities requires high quality and capacity both from the HR side and the information technology system, thereby reducing interest Small–sized ICB to carry out diversified activities in non–traditional activities. In addition, larger Islamic commercial banks have better risk management than smaller banks so that they have a greater opportunity to diversify compared to small banks. 5. CONCLUSION In this study, researchers expanded the research of Lin et al. (2012) using a sample of Sharia Commercial Banks operating in Indonesia in 2010–2017 and providing a detailed description of the benefits of diversifying assets and diversifying income. The researcher used the endogenous switching regression model with the classification of two regimes to categorize Islamic banks into regimes with high and low diversification levels. The results of this study indicate that overall, banks that are in a high asset diversification regime tend to be less sensitive to the fluctuations in the determinants of a net operating margin than banks that do focus strategies, thus providing benefits from conducting diversified activities. 581
15. The results of this study also indicate that operational costs are by far the most important determinant of the margins of sharia commercial banks in Indonesia. Diversifying assets and income both tend to reduce the level of efficiency of Islamic banking in Indonesia. Researchers also found that large–sized Islamic commercial banks have a high probability of diversifying high income compared to small–sized banks. The success of diversification strategies cannot be generalized to all companies, but there are certain conditions and specific differences in financial institutions that can support a successful strategy; there is a financial institution, however, is not successful at other financial institutions. So that in this study, some main implications are given: 1. The results of this study provide information that sharia commercial banks in Indonesia are still less efficient in setting their margins, where the high operational costs tend to cause Islamic commercial banks to set high margins, which could potentially reduce economic activities counterproductive. Therefore, the management of sharia commercial banks needs to improve efficiency in their operational activities and exercise better control of bank risk management. 2. Diversification of assets that are low or concentrated ICB assets against loans tend to increase NOM sensitivity to fluctuations in NOM determinants, especially in financing risks, operational costs and capital. If ICB aims to improve asset quality and maintain its level of capital adequacy, ICB management needs to carry out a diversification strategy on its assets compared to focusing strategies. 3. The results of this study can be used as a reference for policymakers, especially the government if they want to build the ideal NOM ratio for the Islamic banking industry by establishing regulations relating to the level of efficiency of Islamic banking in conducting financial intermediation activities especially when conducting high–income diversification activities and strategies focus on financing. REFERENCE 1. Abedifar, P., Molyneux, P., & Tarazi, A. (2013), 'Risk in Islamic Banking', Review of Finance, 17(6), 2035–2096. doi:10.1093/rof/rfs041. 2. Ascarya, A., & Yumanita, D. (2010). The Determinants of Net Interest Margin in Conventional and Islamic Banks in Indonesia. Paper presented at the International Conference on Eurasian Economies 2010. 3. Baele, L., De Jonghe, O., & Vander Vennet, R. (2007), 'Does the Stock Market Value Bank Diversification?', Journal of Banking & Finance, 31(7), 1999–2023. doi:10.1016/j.jbankfin.2006.08.003. 4. Berger, A. N., Bonime, S. D., Covitz, D. M., & Hancock, D. (2000), 'Why Are Bank Profits So Persistent? The Roles of Product Market Competition, Informational Opacity, and Regional/Macroeconomic Shocks', Journal of Banking & Finance, 24(7), 1203–1235. doi:10.1016/s0378–4266(99)00124–7. 5. Birchwood, A., Brei, M., & Noel, D. M. (2017), 'Interest margins and bank regulation in Central America and the Caribbean', Journal of Banking & Finance, 85, 56–68. doi:10.1016/j.jbankfin.2017.08.003. 6. Brock, P. L., & Rojas Suarez, L. (2000), 'Understanding the behavior of bank spreads in Latin America', Journal of Development Economics, 63(1), 113–134. doi:10.1016/s0304–3878(00)00102–4. 7. Carbú–Valverde, S., Rodrớguez–Fernỏndez, F., & Udell, G. F. (2009), 'Bank Market Power and Sme Financing Constraints', Review of Finance, 13(2), 309–340. doi:10.1093/rof/rfp003. 8. Carbú Valverde, S., & Rodrớguez Fernỏndez, F. (2007), 'The Determinants of Bank Margins in European Banking', Journal of Banking & Finance, 31(7), 2043–2063. doi:10.1016/j.jbankfin.2006.06.017. 582
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