THE 10
thISLAMIC BANKING, ACCOUNTING, AND FINANCE INTERNATIONAL CONFERENCE 2022
(iBAF 2022)
Long-Run Relationship between Islamic Financing Products and Banks’
Financial Performance Dg Safrina Ag Budin
Faculty of Business, Economics and Accountancy, Universiti Malaysia Sabah (UMS) Jalan UMS, 88400 Kota Kinabalu, Sabah Malaysia
E-mail: [email protected]
Syed Musa Syed Jaafar Alhabshi
IIUM Institute of Islamic Banking and Finance (IIiBF), International Islamic University (IIUM) Block D, Level 2, KICT Building, Jalan Gombak 53100 Kuala Lumpur Malaysia
E-mail: [email protected]
Anwar Hasan Abdullah Othman
IIUM Institute of Islamic Banking and Finance (IIiBF), International Islamic University (IIUM) Block D, Level 2, KICT Building, Jalan Gombak 53100 Kuala Lumpur Malaysia
Rosle Mohidin
Faculty of Business, Economics and Accountancy, Universiti Malaysia Sabah (UMS) Jalan UMS, 88400 Kota Kinabalu, Sabah Malaysia
Abstract
Banks are diversifying their revenue streams to include a greater proportion of non-interest- earning products. Changes in the product mix offered by banks make them more competitive and capable of generating more stable and sustainable income, which encourages banks to develop and promote new products that improve their financial performance. The increasing demand for Islamic banking products has heightened the competitive environment in the commercial banking industry, particularly in terms of the benefits of banks' product diversification strategy. Islamic banking adheres to Shariah principles, and its products are Shariah-compliant. However, there is a lack of understanding and knowledge about the specific contracts or products offered by Islamic banks. This study investigates the long-run relationship in Islamic bank financing products to improve the banks' financial performance. The financial data of sixteen Malaysian Islamic banks were gathered for this study from the Islamic Financial Services Board's Prudential and Structural Islamic Financial Indicators (PSIFIs) database (IFSB).
The Autoregressive Distributed Lags (ARDL) model was used, with data spanning from 2014 to 2018. The findings revealed that Bai Bithaman Ajil, Ijarah, Musyarakah, and other Shariah-compliant products have a significant long-term impact on the performance of return on asset (ROA), financing income (RFIN), gross non-performing financing (GNPF), and net profit margin (NPM). It indicates that the financing model of Islamic banks in Malaysia is diversifying. The overall findings suggest that the diversification strategy in financing assets product may have a significant long-term impact on the financial performance of Islamic banks.
Keywords: Islamic Banking; Diversification Strategy; Bank Performance
1. Introduction
Traditional income is more likely to be affected in the current economic crisis, potentially increasing the banks' expenses on bad debts or loan-loss provision, which will affect the banks' net income. Non-traditional sources of income have increased in proportion globally over the years, reducing reliance on traditional sources, which are more cyclical (Edwards & Mishkin, 1995; Smith et al., 2003). The changing behaviour of income generation benefits institutions' success because non-interest income contributes a larger share of bank earnings. These activities now contribute to the bottom line of any banking institution. It has become a popular way to diversify banking returns and is regarded as a positive initiative to improve income stability and lower earnings volatility.
Hidayat et al. (2012) claimed that while product diversification increased risk for large banks, it reduced risk
for small banks. Greater reliance on commission and fee activities was linked to higher bank risk in terms of earnings and volatility, especially for smaller banks. The impact of product diversification on bank risk is determined by the size of a bank's assets, which may be positively related to bank risk for large-sized banks.
Because there have been few studies of non-interest-based income in Asian countries (Pennathur et al., 2012;
Hidayat et al., 2012), the findings contradict those of other regions. The findings differ due to differences in samples, methods, and their results, which are primarily due to differences in the market environment. Many claims have been made about the performance and risk level of banking institutions. Non-interest income activities can reduce the volatility and risk of bank profits. As a result, the activities are worth investigating in order to comprehend the relationship between risk and return. It is intriguing to investigate this type of banking in order to determine the significance of product income-based activities in Malaysian banking institutions.
There is a scarcity of research on diversification strategies in Islamic banking assets (contracts) and liabilities products (contracts). Thus, by focusing on Malaysia, this study aims to provide a counterpoint to previous studies, with additional variables. It is worthwhile to investigate these activities in order to comprehend the impact of product diversification on bank performance. In this context, the purpose of this study is to fill a gap in the literature by focusing on the role of bank product diversification strategy in Malaysian Islamic banks. Therefeore, this study investigates the long-run relationship of the financing assets products such as Bai Bithaman Ajil, Ijarah, Istisna, Mudharabah, Murabahah, Musyarakah, and other shariah-compliant products on the financial performance of Islamic banks. Concerning the aforementioned objectives, questions have been raised regarding the impact of the banks' asset diversification strategy based on Islamic products (contracts) on the financial performance of Islamic banks in Malaysia.
2. Literature Review
In a dual banking system, income sources may differ, particularly between conventional and Islamic commercial banks. Interest-based income is defined as any income that earns or charges interest. Islamic banks' financial and investment assets generate non-traditional income activities with no interest. These are Islamic contracts (products) offered by Islamic banks such as Bai Bithaman Ajil, Ijarah, Mudharabah, Murabaha, Musyarakah, Istisna, Sukuk, and others. Many of the sources of income for Islamic banks are similar to those found in conventional commercial banks, but they differ in terminology as well as the financial and legal structures under which the banks operate (Beck et al., 2010; Khan, 2010). Due to its distinct philosophical and functional perspective, Islamic banking interprets the term "income" differently than conventional banking. Islamic banking operations adhere to Shariah rules, which require that all income sources be free of interest (riba or usury). Muslims are not allowed to engage in any business dealings that involve interest-based activities or other prohibited activities. The basis for the prohibition of interest is stated explicitly in four different Surahs of the Qur'an (Ariff, 1998).
In order to increase revenue, more banking institutions have shifted away from traditional (interest-based income) approaches and toward non-traditional (non-interest-based income) income-generating activities (Jaffar et al., 2014). Banking institutions have altered their financial activities in order to reap the benefits of the income diversification strategy, which promotes profitability and income stability. Even though non-interest income has grown in importance, it has not completely compensated for reductions in the interest portion. According to Stiroh and Rumble (2006), increased exposure to non-interest income has resulted in diversification benefits for conventional banks, but the activity is more volatile and less profitable than lending. Nonetheless, it has been claimed that non-interest income will help to stabilise total operating income (Smith et al., 2003).
Pennathur et al. (2012) further argued that income diversification had benefited India’s public sector banks in which non-interest-based income significantly reduced the risk for public sector banks, but it eventually increased the risk for private sector banks. Hidayat et al. (2012) claimed that a product diversification strategy increased the risk for large banks, but it has helped reduce the risk for small banks. Greater reliance on commission and fee activities was associated with higher bank risk in earnings and volatility, particularly for smaller banks. The effect of product diversification on bank risk will depend on a bank’s asset size in which may positively relate to bank risk for large-sized banks. Since there are relatively little researches (Pennathur et al., 2012; Hidayat et al., 2012)
income- based activities, but this feature has not been discussed in the context of conventional banks. Considering the objective of Islamic banking, it may not play an intermediary role as does conventional banking. In general, Islamic banks act as a business entity. They focus more on investment activity rather than becoming an intermediary. It has led to studying the main income activities in Islamic banks and how they perform business according to Islamic contracts.
3. Materials and Methods
According to the structural indicators (SIFI) in the IFSB compilation guidelines 2015, Islamic banks are classified into two types: stand-alone institutions offering Islamic financial services (IIFS) or full-fledged Islamic banks, and windows, which include Islamic banking branches, divisions, and Islamic windows operated by conventional banks. In Malaysia, there are sixteen Islamic banks, including locally owned Islamic banks, subsidiaries, and international owned Islamic banks. This study used aggregate bank data generated by compiling and consolidating the quarterly value of registered individual Islamic banks in Malaysia for a period 2014 to 2018.
It was analysed using EViews 10 for Autoregressive Distribution Lags (ARDL) model. The ARDL model was chosen for this study due to the short period of data used for time series analysis. For decades, this model was used to examine how variables change over time.
The return on asset (ROA), gross non-performing financing (GNPF), net profit margin (NPM), and financing- based income (RFIN) are the data used in this study to represent the banks' financial performance. The dependent variables were chosen based on previous literature financial performance proxies and income diversification proxies in Islamic banking institutions. Some of the selected dependent variables have not been studied previously, but they are being considered for Islamic banks' financial performance measurement.
Independent variables are products (contracts) offered by Malaysian Islamic banks. The variables' definitions and calculations are based on the prudential and structural Islamic financial indicators (PSIFIs) guidelines (IFSB, 2015).
This study adds to the literature by investigating the contribution of Islamic banking products in Malaysia using a variety of metrics. Return on assets (ROA) (Rosly & Bakar, 2003; Detragiache et al., 2018), return on equity (ROE) (Ramlan & Adnan, 2016, Rabaa & Younes, 2016) and operating profit margin (OPM) have all been used to assess bank performance (Nawaz & Bardai, 2017). Thus, the performance of Islamic banks in Malaysia is estimated based on the various activities in bank financing assets. The model specifications developed in this study reflect the selected variables that measure the financial performance of Islamic banks in Malaysia. Models in Islamic banks were chosen based on income diversification. The following models were used in this study:
𝛶 ≡ 𝛼 + 𝛽1(𝐹𝐴_𝐵𝐵𝐴) + 𝛽2(𝐹𝐴_𝐼𝐽𝑅) + 𝛽3 (𝐹𝐴_𝐼𝑆𝑁) + 𝛽4 (𝐹𝐴_𝑀𝐷𝐵) + 𝛽5(𝐹𝐴_𝑀𝑅𝐵) + 𝛽6 (𝐹𝐴_𝑀𝑆𝑌)+
𝛽7 (𝐹𝐴_𝑂𝑇𝐻) + 𝜀
ϒ represents the measures of the banks’ financial performance, namely return on asset (ROA), financing income (RFIN), net profit margin (NPM) and gross non-performing financing (GNPF). 𝛼 represents the intercepts or slope of the dependent variables, 𝛽1−7 represents the coefficients of the independent variables and 𝜀 represents the error term. The hypotheses were developed to identify the diversified product offered by banking institutions that may significantly impact the Islamic banks’ financial performance. Hypotheses consist of Islamic banks’
products in Malaysia. Based on Table 1, hypotheses are developed to identify the long-run equilibrium relationship between financial performance and the explanatory variables. These are the significant activities that generate income in Islamic banking institutions. Hypotheses H1 - H7 were developed for financing assets (FA) based on the market’s contracts and products. The assumption is, the list of products for financing activities may have a significant long-run relationship with ROA, RFIN, GNPF and NPM. Return on asset (ROA), return on equity (ROE) and net profit margin (NPM) are used frequently as financial performance indicators. In this study, financing income (RFIN) were used exclusively for financing assets in measuring financial performance and gross non- performing financing (GNPF), because financing activities may expose the banking institutions to credit risk.
Table 1. Hypotheses of The Relationship Between Banking Products and Bank’s Financial Performance
Hypothesis Research Hypotheses
Ha: Selected bank’s financing assets variables have a significant long-run equilibrium relationship with Islamic banks’ ROA, RFIN, GNPF and NPM in Malaysia.
H1: Bai Bithaman Ajil products have a significant long-run equilibrium relationship with the Islamic banks’ ROA, RFIN, GNPF and NPM in Malaysia.
H2: Ijarah products have a significant long-run equilibrium relationship with the Islamic banks’ ROA, RFIN, GNPF and NPM in Malaysia.
H3: Istisna products have a significant long-run equilibrium relationship with the Islamic banks’ ROA, RFIN, GNPF and NPM in Malaysia.
H4: Mudharabah products have a significant long-run equilibrium relationship with the Islamic banks’ ROA, RFIN, GNPF and NPM in Malaysia.
H5: Murabahah products have a significant long-run equilibrium relationship with the Islamic banks’ ROA, RFIN, GNPF and NPM in Malaysia.
H6: Musyarakah products have a significant long-run equilibrium relationship with the Islamic banks’ ROA, RFIN, GNPF and NPM in Malaysia.
H7: Other shariah-compliant products have a significant long-run equilibrium relationship with the Islamic banks’ ROA, RFIN, GNPF and NPM in Malaysia.
4. Results and Discussion
This study investigates the long-run impact of product diversification strategy on the financial performance of Islamic banks. A thorough analysis has been performed to identify the correlation between bank products and performance for a five-year period.
Table 2. Descriptive Analysis of Dependent Variables
ROA LOG(RFIN) GNPF NPM
Mean 0.0104 8.6005 0.0130 0.3948
Median 0.0104 8.7048 0.0130 0.3918
Maximum 0.0120 9.3569 0.0140 0.4462
Minimum 0.0095 7.7488 0.0120 0.3424
Std. Dev. 0.0007 0.5409 0.0006 0.0257
Skewness 0.5698 -0.3592 -0.1127 0.1846
Kurtosis 2.3604 1.8088 1.8284 2.8545
Jarque-Bera 1.2808 1.4513 1.0676 0.1181
Probability (P) 0.5271 0.4840 0.5864 0.9426
Observations 18 18 18 18
Table 2 summaries the statistical features of each dependent variable in this study. The descriptive statistics of dependent variables reveal that the ROA has the lowest mean as of 0.0104 and followed by GNPF for 0.0130 and NPM for 0.3948. LOG(RFIN) has the highest mean of 8.6005. The results show a similar pattern in the maximum and minimum value of the dependent variables, but at a different value, as shown in the table. ROA, GNPF and NPM has lesser value due to the data percentage form. Therefore, RFIN is the change-based log values. GNPF shows the lowest standard deviation value of 0.0006 closely followed by ROA for 0.0007 and NPM for 0.0257 and LOG(RFIN) show a slightly higher value of standard deviation. Skewness, kurtosis and Jarque-Bera are used to express the normal distribution of the data and the peak of the tail of each variable. The probability value of more than zero indicates that there is a possibility of occurrence and a certainty to use the selected variables as a dependent variable in this study.
Table 3. The Descriptive Analysis Of The Financing Assets LOG(FA_B
BA)
LOG(FA _IJR)
LOG(FA _ISN)
LOG(FA_
MDB)
LOG(FA_
MRB)
LOG(FA_
MSY)
LOG(FA_
OTH)
Mean 11.1900 11.2741 7.5544 4.2635 11.7223 10.3665 11.2776
Median 11.1769 11.2876 7.5484 4.2848 11.7824 10.3616 11.3059
Maximum 11.3305 11.3130 7.6972 4.3881 12.2159 10.8345 11.5452
The log value is also used for financing assets variables in this analysis to respond to the percentage change in the values.
Table 4. Correlation Matrix Between Financing Assets LOG(FA_B
BA)
LOG(FA_
IJR)
LOG(FA_I SN)
LOG(FA_M DB)
LOG(FA_M RB)
LOG(FA_M SY)
LOG(FA_O TH)
LOG(FA_BBA) 1.0000
LOG(FA_IJR) -0.6754 1.0000
LOG(FA_ISN) -0.2289 0.7310 1.0000
LOG(FA_MDB) 0.9162 -0.4631 0.0387 1.0000
LOG(FA_MRB) -0.9611 0.8136 0.3835 -0.8285 1.0000
LOG(FA_MSY) -0.9722 0.7360 0.2686 -0.8755 0.9889 1.0000
LOG(FA_OTH) -0.9209 0.8553 0.4708 -0.8179 0.9559 0.9284 1.0000
The results of pairwise correlation matrix analyses for selected financing asset variables are shown in Table 4. It demonstrates a strong positive and negative correlation between independent variables in Malaysian Islamic banks' financing assets, with a coefficient correlation value greater than 0.90. Bai bithaman ajil products have a strong positive correlation with mudharabah of 0.9162 and a strong negative correlation with musyarakah, murabahah, and other assets of -0.9722, -0.9611, and -0.9209, respectively. Murabahah, on the other hand, has a high positive correlation with musyarakah and other financing assets, with values of 0.9889 and 0.9559, respectively.
Despite the fact that the products in the model have a high correlation, the results do not reflect the model's redundant information due to the multicollinearity rule of thumb (Kumari, 2008; Schober et al., 2018). The explanations are that those contracts are differentiated based on Islamic definitions that are conceptually different from one another. Thus, the option of eliminating variables is not used in this study. As a result, all products are regarded as exclusive to Islamic banks. As a result, all variables are used for analysis, with the assumption that there is no causal relationship between the variables and that they may only have a complementary relationship to run the banking activities.
Table 5. Unit Root Test for Dependent Variables Variables Name
On Levels On First Differences Intercept and Trend Intercept and No Trend
ADF PP ADF PP
ROA -3.0255 -2.9862 -5.6125*** -6.1947***
LOG(RFIN) -2.3291 -9.1987*** -2.2230** -10.8841***
GNPF -2.8891 -6.6771*** -5.6122*** -7.3726***
NPM -2.9143 -3.3196* -5.7188*** -6.0802***
The results in Table 5 show that LOG(RFIN), GNPF and NPM are integrated on levels I (0), for the assumptions of existence of intercept and trend, while ROA is integrated on first difference I (1), for the assumptions of the existence of intercept with no trend. NPM is stationary on levels at the significance level of 10%. LOG(RFIN) and LOG(GNPF) are stationary on levels at the significance level of 1%. The PP test is the appropriate test for the dependent variables in I (0). Thus, ROA is stationary on the first difference at the 1% significance level for both ADF and PP test. Overall, the unit root test shows a mixed result of stationary level for each selected variable on levels I (0) and the first difference I (1). Thus, we conclude that the bounds test analysis is required to examine the long-run relationship among selected dependent variables.
Table 6 shows the unit root test results of the bank financing assets. The results reveal that LOG(FA_BBA), LOG(FA_IJR) and LOG(FA_ISN) are stationary on a level at a respective significance level of 1%, 5% and 1%.
LOG(FA_MDB), LOG(FA_MSY) and LOG(FA_OTH) are stationary on the first difference for both ADF and PP test at the significance level of 10%. LOG(FA_MRB) stationary on first difference only for PP test. Thus, the bounds test analysis is required for the financing assets model.
Table 6. Unit Root Test for Financing Assets Variables Name
On Levels On First Differences Intercept and Trend Intercept and No Trend
ADF PP ADF PP
LOG(FA_BBA) -5.5300*** -5.5380*** -7.9721*** -8.0964***
LOG(FA_IJR) -3.6795** -2.6922 -1.8525 -1.8525
LOG(FA_ISN) -7.4270*** -2.2615 -2.8161* -2.4985
LOG(FA_MDB) -0.8355 -0.2642 -2.9087* -2.9220*
LOG(FA_MRB) -1.3967 -0.6125 -1.3118 -2.6247*
LOG(FA_MSY) -0.3922 -0.4900 -2.9658** -2.9429*
LOG(FA_OTH) -2.5243 -2.0306 -2.9299* -2.8383*
The optimal lags of the ARDL model for financing assets are shown in table 7. The results show that the optimal model for ROA, RFIN, GNPF and NPM with no serial correlation (P-value > 0) problem is the one that uses one lag-length as confirmed by the highest value based on AIC. This study follows the AIC criterion model for the model specification of ARDL.
Table 7. Optimal Lag of The ARDL Model for Financing Assets
Variable Optimal lag LogL AIC* BIC HQ Adj. R-sq Model Specification ROA 1 144.1564 -15.3125 -14.6263 -15.2443 0.9632 ARDL (1, 1, 1, 1, 0, 1, 0, 1) RFIN 1 15.3893 -0.2811 0.3561 -0.2178 0.8452 ARDL (1, 1, 1, 0, 0, 1, 1, 1) GNPF 1 140.9622 -14.8191 -14.0839 -14.7460 0.9122 ARDL (1, 1, 1, 1, 1, 1, 1, 1) NPM 1 57.87852 -5.51512 -4.97598 -5.46153 0.73773 ARDL (1, 1, 0, 1, 0, 1, 0, 0)
Table 8. Bound Test Results of Financing Assets
Dependent Variables F-stat Case
Sig. level Lower Bound Upper Bound
ROA 46.5588
(Unrestricted Constant and No Trend)
1% 2.96 4.26
5% 2.32 3.50
10% 2.03 3.13
RFIN 21.3764
(No Constant and No Trend)
1% 2.54 3.91
5% 1.97 3.18
10% 1.70 2.83
GNPF 23.9069
1% 2.54 3.91
5% 1.97 3.18
10% 1.70 2.83
NPM 8.2333
(No Constant and No Trend)
1% 2.54 3.91
5% 1.97 3.18
10% 1.70 2.83
Table 8 summarises the results of the bounds test for the financing assets model and selected dependent variables in each case. In this study, ROA assumed unrestricted constant and no trend. While RFIN, GNPF and NPM investigated the long-run relationship using a case of no constant and no trend. At all significance levels of 1%, 5%, and 10%. The F-statistic with the values of ROA, RFIN, GNPF and NPM is greater than the lower and
Table 9. Long-Run Form for the Selected ARDL Model of Financing Assets Selected Based on (AIC) Criterion Dependent
variable (s)
Independent variable FINANCING ASSETS (FA)
Variable LOG(FA_B
BA) LOG(FA_
IJR) LOG(FA_I
SN) LOG(FA_M
DB) LOG(FA_M
RB) LOG(FA_M
SY) LOG(FA_O
TH) Coefficient 0.0131* -0.0226** -0.0146*** -0.0001 0.0059 -0.0110 0.0177***
ROA Std. Error 0.0058 0.0052 0.0024 0.0032 0.0048 0.0062 0.0022
t-Statistic 2.2500 -4.3240 -6.1091 -0.0293 1.2406 -1.7838 8.0307
Prob. 0.1099 0.0228 0.0088 0.9785 0.3029 0.1725 0.0040
Coefficient -48.0280*** 80.3349** 1.3560 1.9760 -24.3915** 15.9277** -22.7281**
RFIN Std. Error 10.5778 18.5325 2.7050 3.1882 5.9008 4.1797 6.6741
t-Statistic -4.5405 4.3348 0.5013 0.6198 -4.1336 3.8107 -3.4054
Prob. 0.0105 0.0123 0.6425 0.5690 0.0145 0.0189 0.0271
Coefficient -0.0025 0.0220* -0.0030 -0.0097* -0.0079 0.0062 -0.0100**
GNPF Std. Error 0.0041 0.0055 0.0015 0.0027 0.0029 0.0029 0.0022
t-Statistic -0.6117 3.9979 -1.9504 -3.5468 -2.7066 2.1133 -4.5611
Prob. 0.6030 0.0572 0.1904 0.0711 0.1137 0.1689 0.0449
Coefficient 2.1831* -1.5534 -0.9977* -0.9442 1.7740* -1.9796* 0.4425
NPM Std. Error 0.9926 0.8732 0.4212 0.5494 0.8470 0.9615 0.2974
t-Statistic 2.1993 -1.7789 -2.3690 -1.7186 2.0945 -2.0590 1.4877
Prob. 0.0702 0.1256 0.0556 0.1365 0.0811 0.0852 0.1874
Table 9 summarises the long-run relationship between financing asset variables and Islamic bank dependent variables in Malaysia. It demonstrates that the dependent variables and the financing asset variables have mixed relationships. Return on assets (ROA) has a significant positive relationship with bai bithaman ajil, and other shariah-compliant assets at the significance levels of 10% and 1%, respectively, but a significant negative relationship with ijarah and istisna at the significance levels of 5% and 1%, respectively, in the long run.
Mudharabah, murabahah, and musyarakah have no long-run relationship with return on asset. It suggests that in the long run, bai bithaman ajil (BBA), ijarah (IJR), istisna (ISN), and other shariah compliant (OTH) financing assets products may contribute to the return on asset (ROA) in Malaysian Islamic banks. As a result, this may be considered one of the best banking products for analysing ROA performance over time. Financing-based income (RFIN) results show a significant positive correlation with ijarah and musyarakah at the 5% significance level, and a significant negative correlation with bai bithaman ajil, murabahah, and other assets at the 1%, 5%, and 5%
significance levels, respectively. Istisna and mudharabah have no significant influence on financing-based income (RFIN) in the long-run relationship framework. Thus, the financing-based income (RFIN) of Islamic banks in Malaysia can be measured in the long run using bai bithaman ajil (BBA), ijarah (IJR), murabahah (MRB), musyarakah (MSY), and other (OTH) financing products. Gross non-performing financing (GNPF) results show that it has only positive relationship ijarah at the 1% significance level, and adverse relationship with mudharabah and other assets at the respective significance level of 1% and 5% in the long-run. Bai Bithaman Ajil istisna, murabahah and musyarakah has no relations with GNPF in the long- run.
This suggests that in the long run, ijarah (IJR), mudharabah (MDB), and other (OTH) financing products represent the GNPF performance in Malaysian Islamic banks. In general, gross non-performing financing refers to the risk of payment default in bank financing products. As a result, a higher level of GNPF may expose banks to a high credit risk. Net profit margin is the final dependent variable in determining the long-run relationship of financing assets (NPM). At the significance level of 10%, it shows that NPM has a positive long-run relationship with bai bithaman ajil and murabahah and a negative long-run relationship with istisna and musyarakah in all products. This means that ijarah, mudharabah, and other financing products have no long-term impact on NPM performance. It indicates that the performance of the net profit margin (NPM) in Malaysian Islamic banks is influenced by banking products such as bai bithaman ajil (BBA), ijarah (IJR), murabahah (MRB), and musyarakah (MSY).
In summary, table 10 shows that the long-run performance of return on asset (ROA) in financing assets model supported hypotheses H1, H2, H3, and H7. It demonstrates that in the long run, ROA has a positive relationship with bai bithaman ajil and other Shariah-compliant, but a negative relationship with ijarah and istisna. This suggests that bai bithaman ajil and other shariah-compliant financing products have contributed to the performance of ROA in Malaysian Islamic banks. However, ijarah and istisna products have no long-term impact on ROA performance.
Overall, the ROA results show that bai bithaman ajil and other Shariah- compliant products have a diversification effect in financing activities, implying that banks should increase their activities in those products to improve performance.
The results of the financing-based income (RFIN) model supported hypotheses H1, H2, H5, H6, and H7 for a long-run. It demonstrates that RFIN has a positive long-run relationship with ijarah and musyarakah, but a negative relationship with bai bithaman ajil, murabahah, and other Shariah-compliant. Overall RFIN results show that ijarah and musyarakah products have a diversification effect and contribute to the long-run performance of financing- based income. The results for gross non-performing financing (GNPF) in financing models show that it supported the hypotheses H2, H4, and H7 in the long run. However, in the long run, the GNPF has a negative relationship with mudharabah and other Shariah-compliant products. Overall GNPF results show that the ijarah product contributes to GNPF's long-term performance.
Finally, the financing model's net profit margin (NPM) results show that it supported the hypotheses H1, H3, H5, and H6 in the long run. BBA and murabahah have positive relationship with NPM. It shows that the bai bithaman ajil product is useful for measuring NPM performance and the murabahah product can also be used in the long run.
Table 10. Results Summary of Financing Assets
Long Run Relationship Between Financing Assets and Islamic Bank Financial Performance in Malaysia Dependant
variable (s)
Variable (s) H1
LOG(FA_BB A)
H2 LOG(FA_I JR)
H3
LOG(FA_IS N)
H4 LOG(FA_
MDB)
H5 LOG(FA_
MRB)
H6 LOG(FA_
MSY)
H7 LOG(FA_
OTH) Results Positive* Negative** Negative*** Negative Positive Negative Positive***
ROA Not Not
Notes Supported Supported Supported Support Not Support Supported Supported Result Negative*** Positive** Positive Positive Negative** Positive** Negative**
RFIN
Notes Supported Supported Not
Support Not
Support Supported Supported Supported Result Negative Positive* Negative Negative* Negative Positive Negative**
GNPF Not
Notes Not Support Supported Not Support Supported Not Support Supported Supported Result Positive* Negative Negative* Negative Positive* Negative* Positive
NPM Not Not Not
Notes Supported Support Supported Support Supported Supported Support
5. Conclusion
The purpose of this study was to discover the long-term diversification strategy in Islamic banking institutions, specifically banking products that have a significant impact on the banks' financial performance. Islamic banking institutions are commercial entities that provide Shariah-compliant products. Islamic banking institutions provide a variety of compliant contracts subject to approval by the country's policymakers. The Shariah Advisory Shariah- Council (SAC), the authoritative body in Bank Negara Malaysia, is responsible for validating all Islamic banking products to ensure they are Shariah-compliant. Thus, the contracts offered by Malaysian Islamic banking institutions, namely Bai Bitahaman Ajil, Ijarah, Mudharabah, Murabahah, Musyarakah, Istisna, are widely used for financing income-generating activities. Profitability of banks is determined by the allocation of assets, liabilities, and capital. The impact of diversification varies depending on the products (contracts) offered by Malaysian Islamic banks. The existence of a diversification strategy in bank income activities has been supported by testing hypotheses and hypotheses.
Overall, bai bithaman ajil, ijarah, musyarakah, and other Shariah-compliant products have a significant long- term impact on the performance of ROA, RFIN, GNPF, and NPM. It indicates that the financing model of Islamic banks in Malaysia is diversifying. The overall findings suggest that the diversification strategy in financing assets product may have a significant long-term impact on the performance of Islamic banks. Products with a negative sign or that are insignificant should be considered as part of the banks' risk management strategy, which includes
diversification in terms of income stream patterns. It expects to serve as a guide for the managers or management teams of Islamic banks in making wise diversification decisions that will improve the bank's performance. The findings may also aid in decisions about the types of hybrid Shariah products that generate revenue for banks.
Policymakers or SAC are better positioned to determine which products should be promoted to increase the profitability of the Islamic banking industry.
Acknowledgement
The authors would like to express appreciation for the support of Universiti Malaysia Sabah.
References
Abrar, T., Ahmed, F. & Kashif, M. 2018. Financial Stability of Islamic Versus Conventional Banks in Pakistan. Al-Iqtishad: Jurnal Ilmu Ekonomi Syariah (Journal of Islamic Economics). 10 (2). pp. 341 – 366. P-ISSN: 2087-135X; E-ISSN: 2407-8654.
Ahmed, H. 2011. Product Development in Islamic Banks. Edinburgh Guides to Islamic Finance. UK. Edinburgh University Press. ISBN:
9780748639526.
Ariff, M. 1988. Islamic Banking in Southeast Asia: Islam and The Economic Development of Southeast Asia. Singapore: Institute of Southeast Asian Studies. ISBN: 9971988984.
Ariff, M. 1998. “Islamic Banking”. Asian-Pacific Economic Literature, 2 (2), pp. 48-64. Ariff, M. 2017. Islamic Finance in Malaysia: Growth
& Development. Kuala Lumpur. Pearson Malaysia. ISBN: 9789673497379.
Beck, T., Demirgüç-kunt, A. & Merrouche, O. 2013. “Islamic vs Conventional Banking: Business Model, Efficiency, and Stability”. Journal of Banking and Finance. 37. pp. 433-447. Doi: http://dx.doi.org/10.1016/j.jbankfin.2012.09.016
Chen, N., Liang, H. & Yu, M. 2018. Asset Diversification and Bank Performance: Evidence from Three Asian Countries with a Dual Banking System. Pacific-Basin Finance Journal.52. pp. 40-53. Doi: 10.1016/j.pacfin.2018.02.007.
Cihak, M. and Hesse, H. 2010. “Islamic Banks and Financial Stability: An Empirical Analysis”.
J Financ Serv Res., 38, pp. 95–113.
Demirguc-kunt, A. & Huzainga, H. 2010. “Bank Activity and Funding Strategy”. Journal of Financial Economics. 98.
Detragiache, E., Tressel, T. & Turk-Ariss, Rima 2018. Where Have All the Profits Gone? European Bank Profitability Over the Financial Cycle. IMF Working Paper. WP/18/99. DeYoung, R. & Rice, T. 2004. “How Do Banks Make Money? The fallacies of Fee Income”, Economic Perspective, 4th Quarter, Federal Reserve Bank of Chicago, pp. 34-51.
DeYoung, R. and Roland, K. 2001. “Product Mix and Earnings Volatility of Commercial Banks: Evidence from a Degree of Total Leverage Model”. Journal of Financial Intermediation, 10, pp. 54-58.
Hashem, B.,Sujud, H. 2019. Financial Performance of Banks in Lebanon: Conventional vs Islamic. International Business Research. 12(2).
Doi:10.5539/ibr.v12n2p40.
Hidayat, W.Y., Kakinaka, M., & Miyamoto, H. 2012. “Bank Risk and Non-Interest Income in The Indonesian Banking Industry”. Journal of Asian Economics. 23 (4), pp. 335-343.
IFSB. 2015. Compilation Guide on Prudential and Structural Islamic Financial Indicators: Supplement. Retrieved from https://www.ifsb.org.
Isa, S.S.M., Ma’in, M., Hanif, A. 2018. Islamic banks’ fee income, characteristics and risk: Panel data analysis evidence from Indonesia.
Journal of emerging economies and Islamic research. 6(1). pp.6-16.
Jaffar, K., Mabwe, K., & Webb, R. 2014. “Changing Bank Income Structure: Evidence from Large UK Banks? Asian Journal of Finance and Accounting. 6(2). ISSN 1946-052X.
Nawaz, H. & Bardai, B. 2017. Profitability of Islamic Banks: Case of Malaysia. Journal of Islamic Banking and Finance. 34 (3). pp. 90-103.
Nisar, S., Peng, K., Wang, S., & Ashraf, B.N. 2018. The Impact of Revenue Diversification on Bank Profitability and Stability: Empirical Evidence from South Asian Countries. International Journal of Financial Studies. 6(40). Doi:10.3390/ijfs6020040.
Niyimbanira, F. 2013. An Overview of Methods for Testing Short- and Long-Run Equilibrium with Time Series Data: Cointegration and Error Correction Mechanism. Mediterranean Journal of Social Sciences. 4(4). pp. 151-156.
Nkoro, E. & Uko, K. 2016. Autoregressive Distributed Lags (ARDL) Cointegration Technique: Application and Interpretation. Journal of Statistical and Econometric Methods. 5(4).
pp. 63-91.
Pennathur, A. K., Subrahmanyam, V. & Vishwasrao, S. 2012. “Income diversification and risk: Does ownership matter? An Empirical Examination of Indian Banks” Journal of Banking and Finance. 36, pp. 2203-2215.
Olaweraju, O.M. 2018. Income Diversification in Low-Income Sub-Saharan African Countries’ Commercial Banks: A “Blessings” or a
“Curse”? Folia Oeconomica Stetinensia. 18 (2). Doi: 10.2478/foli-2018-0021.
Ramlan, H. & Adnan, M.S. 2016. The Profitability of Islamic and Conventional Bank: Case Study in Malaysia. Procedia Economics and Finance. 35. pp. 359-367.
Rosly, S.A. & Bakar, M.A.A. 2003. Performance of Islamic and Mainstream Banks in Malaysia. International Journal of Social Economics.
30 (12), pp. 1249-1265.
Samail, N.A.B, Zaidi, N.S.B., Mohamed, A.S.b. & Kamaruzaman, M.N. 2018. Determinants of Financial Performance of Islamic Banking in Malaysia. International Journal of Academic Research in Accounting, Finance & Management Sciences. 8 (4), pp. 21-29.
Smith, R., Staikouras, C. & Wood, G. 2003. “Non-Interest Income and Total Income Stability”. Working Paper No. 198. Bank of England. ISSN 1368-5562.
Uppal, R.K. 2010. “Stability in Bank Income through Fee-Based Activities”. Information Management and Business Review, 1 (1), pp. 40-47.
Widarjono, A., Anto, M.B.A. & Fakhrunnas, F. 2020. Financing risk in Indonesian Islamic Rural Banks: Do Financing Products Matter?
Journal of Asian Finance, Economics & Business. 7(9). pp.305-314. Doi: 0.13106/jafeb.2020.
Williams, B., and Prather, L. 2010. “Bank Risk and Return: The Impact of Bank Non-Interest Income.” International Journal of Managerial Finance, 6 (3), pp. 220 – 244.
