The purpose of this study is to assess and contrast the impact of various factors, including both bank-specific and macroeconomic factors, on the financial performance of Islamic and conventional banks (I&CB) in countries with a dual banking system.
A general least square model is applied to a large data set of 103 I&CB operating in the Middle East and North Africa (MENA) region, comprising unbalanced annual panel data spanning the period from 2015 to 2020. The financial performance index (FPI) derived from capital adequacy, asset quality, management efficiency, earnings, and liquidity (CAMEL) ratios is used as the dependent variable.
Key factors, such as overhead expenses, gross domestic product (GDP) and retained earnings, exert a substantial influence on the financial performance of both I&CB. Moreover, the findings suggest that certain parameters, including deposits, inflation and cellular banking usage, significantly impact on the financial performance of conventional banks, while bank size specifically affects the financial performance of Islamic banks.
While this study provides valuable insights, it is essential to acknowledge its limitations. The research focuses on a specific region (MENA) and may not be universally applicable to other geographical areas or banking systems. The study’s findings are based on historical data and might not fully reflect current or future market conditions. Additionally, the choice of variables and methodology may introduce bias or limitations, as with any empirical study. The theoretical implications of the research paper lie in the distinct ethical principles that constitute the foundation of Islamic finance. The ethical opposition to Riba is poised to have extensive implications, influencing market stability, commercial and economic impact and contributing to responsible banking practices within the Islamic banking sector. The study suggests that adherence to these sacred principles not only aligns with ethical considerations but also fosters social responsibility within Islamic banking institutions. This holds significance for broader societal and economic impacts, as responsible banking practices contribute to sustainable and equitable economic development.
The study underscores the significance of efficient overhead cost management for conventional banks, particularly in the context of a rapidly evolving digital banking environment. The call for adaptation and innovation in operational strategies aligns with the broader principles of efficiency and effectiveness emphasized in Islamic finance.
In essence, the theoretical and practical implications of the study surpass the narrow focus on financial performance, resonating with the broader societal and economic landscape within the Islamic banking sector. The integration of ethical principles not only reinforces the unique identity of Islamic finance but also positions it as a model for responsible and sustainable banking practices in the MENA region and beyond.
CAMEL ratios are used to build an FPI to evaluate bank performance, providing a more precise and comprehensive assessment compared to traditional return ratios like return on assets or return on equity. Second, the authors conduct a thorough analysis covering factors across bank-specific, financial and macroeconomic dimensions. Thus, the study stands out by not only examining bank-specific factors but also by considering external factors such as GDP, interest rates and the development of the financial sector. The focus on the MENA region allows us to offer generalizable findings, highlighting distinctions between I&CB and considering a period with boom years (2015–2019) and a recession year (2020).
1. Introduction
Over the past two decades, the global banking sector has encountered significant disruptions and crises (Juergensen et al., 2020). These transformations have not only affected banking operations but have also reshaped the competitive landscape, impacting consumers and business firms (Al Zaidanin, 2020; Huson et al., 2024). Despite financial crises and their associated challenges, the banking sector’s role in providing essential financial services to all stakeholders has remained pivotal. In this context, the empirical determinants of bank performance have garnered the attention of academic researchers, bank managers, supervisors and financial market regulators (Fernandes et al., 2018). As Bawaneh and Dahiyat (2019) assert, a profitable and robust banking sector is more resilient against adverse shocks and plays a vital role in stabilizing and fortifying the financial system. Analyzing a bank’s performance is particularly beneficial in emerging economies, where the banking environment differs significantly from that of developed nations.
From a practical perspective, financial performance indicators are essential for investors and decision-makers when shaping their investment strategies (Boto-García et al., 2021; Abu Huson et al., 2024). Hence, there is a pressing need to study these factors to enhance banks’ profitability (Jaara et al., 2021; Al-Kayed, 2017). Given the myriad factors influencing the banking industry, comprehensive assessments of financial health have become indispensable. For central and local authorities, monitoring banks’ activities is a crucial task for evaluating the economic well-being of a country (Al Zaidanin, 2020). Furthermore, the distinctions between two competing banking models, conventional and Islamic banking, have come under scrutiny, especially in the aftermath of the 2007–2008 financial crises that challenged the resilience of conventional banking (Ahsan and Qureshi, 2022). Although traditional banking has been studied for decades, there has been a significant growth in research on Islamic banking and finance in recent times (Kocenda and Iwasaki, 2022).
The banking sector currently plays a vital role in the social development agendas of the Middle East and North African (MENA) nations, expanding within both the regional financial system and the nation-states themselves (El Khoury et al., 2021). The MENA region comprises 20 nations with a total population of 357.3 million people and has experienced substantial economic growth, accounting for over 5% of global gross domestic product (GDP) (Caporale et al., 2018). This region includes both oil-rich and stable nations, such as Saudi Arabia, Kuwait, Qatar and the United Arab Emirates, as well as areas with challenging conditions, such as Iraq, Syria, Libya and Yemen (Haque and Brown, 2017). Despite its significance, the MENA banking industry has received relatively little attention compared to developed countries. To address this, we have selected nine stable countries from the MENA region, including Jordan, Kuwait, Qatar, the Kingdom of Saudi Arabia, Bahrain, United Arab Emirates, Morocco, Egypt and Tunisia. These countries operate with dual banking systems that include both conventional (CB) and Islamic banks (IB), making it essential to analyze the diverse features of these institutions. This dual banking system provides customers with a wide range of services and products catering to different financial needs and preferences, allowing them to choose between conventional banking, based on interest-based lending and borrowing and Islamic banking, based on profit and loss sharing principles (Anouze et al., 2019).
Islamic finance is a rapidly growing global financial system of increasing importance (Kassim, 2016; Qudah et al., 2024). The rapid development of Islamic finance has created complexity for regulators, emphasizing the need for standardization and harmonized regulation (Grassa, 2015). Namely, Islamic banking, a key component of Islamic finance, presents regulatory challenges due to the different business models (Hassan et al., 2023).
Numerous empirical studies have shown that various internal factors (e.g. overheads, liquidity, leverage ratios, earnings, credit risk, concentration, solvency risk, operating expenses, deposits and bank size) and macroeconomic factors (e.g. GDP, inflation rate, legal interest rate and exchange rate) significantly influence the financial performance of both CB and IB (Rashid and Jabeen, 2016; Matar and Eneizan, 2018; Muhindi and Ngaba, 2018; Quoc Trung, 2021).
This study aims to assess and contrast the impact of various factors on the performance of both Islamic and conventional banks (I&CB) in the MENA region. Specifically, we intend to create a financial performance index (FPI) based on CAMEL parameters and explore how bank-specific, financial and macroeconomic factors affect this index for both types of banks. The period of analysis includes six years, from 2015 to 2020, in which we can find boom years (2015–2019) with a constant GDP variation in the MENA region of 2.1% and a recession year (2020) with a variation of −3.1%.
Our research makes several valuable contributions to the existing literature. First, we use CAMEL ratios to evaluate bank performance, providing a more precise and comprehensive assessment compared to traditional return ratios like return on assets (ROA) or return on equity (ROE). Second, we conduct a thorough analysis covering factors across bank-specific, financial and macroeconomic dimensions. Thus, our study stands out by not only examining bank-specific factors but also by considering external factors such as GDP, interest rates and the development of the financial sector. Third, our focus on the MENA region allows us to offer generalizable findings, highlighting distinctions between I&CB and considering a period with boom years (2015–2019) and a recession year (2020).
The remainder of the study is structured as follows: Section 2 presents the literature review, Section 3 describes the methodology and data, Section 4 reports the empirical results and Section 5 concludes the study and addresses the study’s limitations.
2. Literature review
2.1 Islamic principles
Islamic finance is rooted in six fundamental principles of Islamic law (Shariah). These principles encompass the prohibition of interest (Riba), the obligation to abstain from engaging in criminal or illicit activities and the avoidance of forbidden practices. Moreover, unlike conventional banks, IBs have their operations fully backed by tangible assets. This distinction between the two types of banks holds significant importance, as IB predominantly conduct their activities based on equity-based instruments, emphasizing profit and loss sharing contracts.
In theory, there are fundamental distinctions between the traditional and Islamic banking models. Nevertheless, both models share a common characteristic as profit-oriented institutions (Zarrouk et al., 2016). Despite the disparities in their core principles, the two banking models offer analogous practical banking products. The primary disparity between them lies in the way they generate income, with interest serving as the primary source of revenue for conventional banks (Chen et al., 2018). Conventional banks rely heavily on interest rate differentials between lending and borrowing. In contrast, interest is strictly prohibited in IB in accordance with Islamic law, as the Islamic Shariah explicitly forbids usury, as stated in the Holy Qur’an (Daly and Frikha, 2015; Abasimel, 2023).
I&CB both share the common goal of ensuring an efficient payment mechanism within the economy (Salman and Nawaz, 2018). They also seek to attain profits through project financing. Conventional banks rely on lucrative financing projects in addition to interest fees, as they receive interest whether the project succeeds or faces losses. Conversely, IB operates based on profit and loss sharing principles (Hoepner et al., 2015). Therefore, IB aims to play a meaningful role through their ethical, social and religious dimensions (Abou-Youssef et al., 2015). Islamic finance is distinguished by its connection to tangible assets, aligning it with the real economy (Daly and Frikha, 2015). Furthermore, it adheres to the prohibition of financing activities deemed illicit (haram) by the Islamic Shariah. Such activities encompass the consumption of alcohol, pork and participation in gambling. Islamic finance also eschews dealing with contracts that are ambiguous and contain hidden elements. Encouraging the payment of zakat, a form of almsgiving, is a crucial and vital aspect of Islamic finance. It is through this practice that social justice is upheld and achieved, reflecting one of the pillars of Islam.
2.2 Comparison between Islamic and conventional banks performance
In the realm of banking research, numerous empirical investigations have diligently endeavored to assess and compare the performance of I&CB, transcending geographical boundaries and spanning various temporal frames, using a rich tapestry of statistical techniques. An exemplary demonstration of this analytical rigor can be gleaned from the comprehensive meta-analysis conducted by Wahab and Roslan (2021). The overarching conclusion derived from their comprehensive analysis suggests that, when viewed through a global lens, there is no statistically significant discrepancy in performance between I&CB. Nevertheless, in specific contexts, IBs have exhibited a proclivity for superior performance when compared to their conventional counterparts (Miah and Sharmeen, 2015).
In the domain of performance assessment, two critical metrics, ROA and ROE, have garnered widespread adoption in assessing the operational efficacy of both I&CB. Eminent studies conducted by Choong et al. (2012), Daly and Frikha (2015) and El-Chaarani et al. (2023) underscore the pervasiveness of these performance indicators. It is imperative to illuminate the seminal study conducted by Choong et al. (2012), which delved into the intricate tapestry of the Malaysian banking sector. The study’s findings, intriguingly, unveiled that factors such as liquidity, diversification (concentration) and even credit risk did not exert statistically significant direct impacts on ROA and ROE. This revelation, challenging conventional wisdom, underscores the multifaceted nature of bank performance dynamics.
Notwithstanding, Rashid and Jabeen (2016) introduced a novel perspective by using the FPI as an encompassing yardstick for evaluating banking performance. A cluster of studies has adroitly embraced the CAMELS framework as their lodestar for evaluating and comparing the performance of I&CB. These studies have meticulously scrutinized a gamut of criteria encompassing capital adequacy, asset quality, management efficiency, earnings, liquidity and sensitivity to market risk. Keffala (2018) embarked on this path, wielding the CAMELS framework to illuminate the pivotal role of financial options in enhancing the performance of IB. Another seminal expedition into this realm was undertaken by Ali et al. (2021) within Pakistan’s banking sector, to compare the financial and administrative performance of I&CB. Their findings underscore that both typologies of banks have charted a trajectory of performance improvement within Pakistan’s economic milieu. Notably, IBs have excelled in facets such as asset quality, management adequacy and risk sensitivity, while their conventional counterparts have exhibited robust performance in the domains of capital adequacy and liquidity.
Regarding the independent variables, a substantial corpus of the investigations has leaned on bank-specific and financial ratios as analytical instruments. Eminent contributors to this continuum of research include Akala (2018), Muhindi and Ngaba (2018) and El-Chaarani et al. (2022).
During times of economic turmoil, several key dynamics come into play, contributing to the decline in banking performance. One of the primary factors is the surge in nonperforming loans as individuals and businesses struggle to meet their financial obligations (Nduati and Wepukhulu, 2020; Albalawee et al., 2024). This uptick in defaults places immense pressure on banks’ balance sheets, eroding profitability and capital adequacy (Shahin and El-Achkar, 2016). Furthermore, the tightening of credit markets during economic crises reduces the availability of funds for lending, constraining one of the core revenue streams for banks. Simultaneously, declining asset values, particularly in the real estate sector, can lead to significant write-downs and impairments, further denting banks’ financial health (Casey and O’Toole, 2014; Al-Qudah et al., 2022).
Moreover, El-Chaarani et al. (2022) embarked on a mission to unveil the critical success factors underlying both I&CB, particularly in the context of the COVID-19 pandemic. Notably, their findings revealed that CB demonstrated a superior financial performance during the crisis and adeptly navigated the complexities of financial risk management. This is further supported by the study conducted by Junjunan et al. (2022), which indicated significant differences in financial performance ratios between I&CB during the COVID-19 pandemic. These differences encompassed metrics such as the capital adequacy ratio, nonperforming loans/nonperforming financing, ROA, ROE, operating expenses to operating income and loan to deposit ratio/financing to deposit ratio.
Buallay et al. (2021) investigated in Gulf Cooperation Council (GCC) banks the relationship between financial, operational and market performance in I&CB, using the integrated report index (IRI) as an independent variable and regressing it separately against three performance indicators: ROA, ROE and Tobin’s Q. The results showed that IRI had a positive impact on market performance in CB but negatively affected operational and financial performance. In IB, IRI negatively influenced market performance, with no significant impact on financial or operational performance.
A subset of scholarly endeavors embarked on the complex terrain of macroeconomic factors, seeking to disentangle their intricate influence on bank performance. These studies offer a panoramic vista of the industry dynamics, fusing micro level bank-specific indicators with macro level economic variables. Bilal et al. (2016) used ROA and ROE as the beacons for this exploration, revealing profound insights into the relationships between these factors. Zeitun (2012) juxtaposed bank-specific variables with macroeconomic indicators, unraveling the complex relationship between these elements and the performance of I&CB within the GCC region. This comprehensive inquiry spanning the years 2002 to 2009 illuminated the significant impact of GDP and inflation on banking performance. Additionally, the study unearthed the profound influence of the bank’s size and the cost-to-income ratio on the performance of both I&CB. Rashid and Jabeen (2016), within the context of Pakistan, contributed to this discourse by meticulously scrutinizing the bank-specific and macroeconomic determinants of financial and economic performance. In this vein, operating efficiency, overheads, reserves and deposit concentration were among the pivotal factors under scrutiny by Joseph and Adelegan (2023). The discerning findings of this research underscored the centrality of operating efficiency and the need for prudent control of overheads to enhance the bank’s performance. Serwadda (2018) analyzed the influence of overhead costs on financial performance, showing an adverse effect on the banks’ performance.
To provide a holistic view of the diverse findings and methodological approaches adopted in prior research, Table 1 serves as a compendium of studies dedicated to the comparative analysis of bank performance determinants within these two distinctive banking ecosystems. In our pursuit of a comprehensive analysis, it was essential to select studies that not only closely align with the core focus of our research but also reflect recent developments in the field. We meticulously curated our literature review by prioritizing studies conducted within the past few years in the MENA region, as well as in countries with a dual system, such as Malaysia, Indonesia and Pakistan. The studies focus on the comparison between I&CB, examining variables that closely resemble those investigated in our paper, with a predominant focus on assessing the financial performance of banks. The decision to incorporate these specific studies over others was grounded in the need for relevance, timeliness and direct alignment with our research objectives, thereby enhancing the rigor and applicability of our findings to the banking sector in the MENA region.
Literature overview
| Authors/ years | Dependent variables | Independent variables | Methodology | Main conclusions | Analysis period | Country/region |
|---|---|---|---|---|---|---|
| Choong et al. (2012) | ROA, ROE | Liquidity, credit risk, level of capital, concentration level and size of the bank | Panel data multiple regression models | Higher credit risk will result in lower earnings and lower ROA and ROE ratios. Liquidity and concentration are relatively insignificant. Level of capital and economic conditions do not influence I&CB performance | 2006–2009 | Malaysia |
| Zeitun (2012) | ROA ROE | Bank age, equity, size, reserve/loan ratio, cost-income, foreign ownership, financial development, GDP, inflation | Cross-sectional time-series (panel data) | The bank’s equity increases CB profitability only. Cost-to-income had a negative and significant impact on I&CB’s performance. Size provides evidence of economies of scale in IB using ROE, while it is not significant for CB. Foreign ownership, the bank’s age and banking development have no effect on I&CB’s performance. GDP is positively correlated, while inflation is negatively correlated to the bank’s profitability | 2002– 2009 | GCC countries |
| Riaz and Mehar (2013) | ROE, ROA | Bank-specific (asset size, credit risk, total deposits to total assets), and macroeconomic determinants (interest rate) | Multiple regression analysis | There is a significant impact of bank specific. Variables and macroeconomic. Indicator on ROE. Credit risk and interest rate also have a significant impact on ROA | 2006–2010 | Pakistan |
| Daly and Frikha (2015) | ROA, ROE and efficiency | Bank size, diversity of income, solvency ratio, market share, government effectiveness, quality regulatory | Data envelopment analysis (DEA) | Significant impact of income diversity, bank size, solvency indicators and loans to assets on the ROE of IB. Market share, solvency indicators and net loans to total assets have significant effects on the ROE for CB Bank size is more significant concerning the ROA of IB | 2005– 2009 | Bahrain |
| Rashid and Jabeen (2016) | Financial performance index (FPI) based on CAMELS’ ratios | Bank-specific variables, macroeconomic factors and financial indicators | GLS regression | Operating efficiency, reserves and overheads are significant determinants of CB performance, whereas operating efficiency, deposits and market concentration are significant in explaining IB performance | 2006–2012 | Pakistan |
| Zarrouk et al. (2016) | ROA, ROE, net profit margin | Liquidity, risk and solvency, efficiency, assets quality, non-financing revenues average assets, cost-to-income ratio. Market capitalization and macroeconomic variables (GDP) | System-generalized method of moment (GMM) | Profitability is positively affected by banks’ cost-effectiveness, asset quality and level of capitalization. Non-financing activities allow IB to earn higher profits. IB performs better when GDP and investment are high. Similarities between determinants of profitability for both I&CB. The inflation rate, however, is negatively associated with IB profitability | 1994–2012 | MENA region |
| Matar and Eneizan (2018) | ROA | Leverage, firm size, liquidity, revenue and profitability | Regression analysis | Liquidity, profitability and revenues are positively related with ROA | 2005–2015 | Jordan |
| Muhindi and Ngaba (2018) | ROA | Descriptive survey design | There is a significant relationship between firm size and the financial performance of commercial banks | 2012– 2016 | Kenya | |
| Buallay et al. (2021) | ROA, ROE and Tobin’s Q | The integrated report index (IRI) | Cross-country analysis | IRI in CB positively affects market performance, while negatively affecting operational and financial performance. For IB, IRI negatively affects market performance, with no discernible effect on either financial or operational performance | 2012–2016 | GCC countries |
| Wahab and Roslan (2021) | ROA | Efficiency, liquidity and risk | Meta-analysis of 73 samples of past journals and published thesis | There is no significant difference of performance between I&CB. Better performance of IB in comparison to CB. IB performs better during short-term periods while the long-term is dominated by CB. IB can performs better than CB in a region with strong government initiatives and community awareness of Islamic finance | Short-term, medium-term and long-term | Pakistan, Bangladesh and Malaysia |
| El-Chaarani et al. (2022) | ROA, ROE | Capital structure ratios, liquidity ratios, financial risk ratios, profitability and macro factors | Descriptive statistics, T-test, multiple regression and 2SLS and GMM models | There is a significant difference between I&CB during the crisis of COVID-19, where CB presented a higher level of return and liquidity than IB. CB revealed a higher capacity to manage their financial risk. A high level of nonperforming loans, a high inflation rate and a high percentage of nonimportant cost have a negative impact on the financial performance of IB, mainly during the pandemic. A high level of liquidity risk increased the performance of IB banks but this impact falls sharply during the pandemic period | 2017–2020 | GCC countries |
| Junjunan et al. (2022) | ROA, ROE | Independent sample t-test | The independent sample t-test and the Mann–Whitney rank test | There were significant differences in capital adequacy ratio, nonperforming loans/nonperforming financing, ROA, ROE, operating expense to operating income and loan to deposit ratio/financing to deposit ratio for both I&CB. CB tends to have a better financial performance compared to IB during the COVID-19 pandemic | COVID-19 pandemi-c | Indonesia |
| El-Chaarani et al. (2023) | ROA, ROE | Credit risk, liquidity risk, capital structure, managerial efficiency | Multiple regressions, t-test | The COVID-19 pandemic had a negative impact on profitability, leading to an increased credit risk, while it did not significantly affect capital adequacy. Managerial efficiency, bank size and GDP had a positive and significant impact on banks’ return in both periods. Credit risk exerted a negative influence on ROE and ROA. Liquidity risk, capital adequacy and inflation did not significantly impact banks’ returns | 2018–2021 | MENA region |
3. Methodology
This section provides a comprehensive discussion of our methodology, data sources, sample selection and a detailed description of the variables used. To begin, we adopt the performance index developed by Teker et al. (2011) as the foundational model for calculating the FPI for each bank within our sample throughout the study period. The FPI is constructed based on the parameters of the CAMEL framework. Subsequently, this study conducts an empirical analysis by applying generalized least squares (GLS) to identify the factors influencing bank performance. In this analysis, the FPI serves as the dependent variable, while various bank-specific variables and macroeconomic indicators act as independent variables.
In addition to GLS, a panel data model with fixed and random effects has been applied to give robustness to the results obtained with the GLS.
3.1 Data and sample
Our analysis focuses on the financial data of 118 I&CB operating across nine countries in the MENA region during the years 2015 to 2020, the past year of data availability. From 2015 to 2019 the constant variation of GDP in the MENA region was 2.1% showing a boom period while 2020 was a recession year with a variation of −3.1%. Thus, this timeframe allows the study to capture financial performance trends and dynamics in I&CB that were relevant and contemporary for researchers and policymakers. To ensure the integrity of our empirical analysis results, we deliberately excluded banks operating in MENA nations that were grappling with financial crises and instabilities arising from their political and economic situations. Specifically, countries such as Yemen, Djibouti, Iraq, Algeria, Palestine, Libya, Iran, Lebanon and Syria were excluded from our sample selection. In addition, banks with missing data were eliminated and the final sample includes 103 banks, as shown in Table 2 (the detailed list of banks is available on request). We started our analysis of comparison of the financial performance of I&CB applying a mean test (U-Mann Whitney for the period 2015–2019 and t student for 2020), and then, applying the GLS model.
MENA country’s banks
| Country | Conventional banks | Islamic banks | Total |
|---|---|---|---|
| Bahrain | 5 | 5 | 10 |
| Egypt | 10 | 3 | 13 |
| Jordan | 13 | 2 | 15 |
| Kingdom of Saudi Arabia | 7 | 4 | 11 |
| Kuwait | 6 | 5 | 11 |
| Morocco | 6 | – | 6 |
| Qatar | 5 | 3 | 8 |
| Tunisia | 11 | 1 | 12 |
| United Arab Emirates | 12 | 5 | 17 |
| Total | 75 | 28 | 103 |
We obtained the secondary data necessary for our analysis from a reliable source, datastream, a widely recognized and respected source of financial data, often used by researchers, analysts and financial professionals for its comprehensive and reliable information. This rigorous approach to sample selection and data collection ensures the robustness and validity of our findings, allowing us to draw meaningful conclusions regarding the financial performance of banks in the MENA region.
3.2 Dependent variable
The FPI has been developed based on the CAMEL parameters, a method introduced by the organisation for economic co-operation and development, following the method of Rashid and Jabeen (2016) slightly modified (see the definition of the CAMEL parameters in the Appendix). The construction of the FPI is divided into three steps. First, we standardized the values as follows:
where µjt denotes sample mean, σjt is the standard deviation of the CAMEL’ parameter (jth indicator) at time t and βijt denotes the individual ratio of each CAMEL’ parameter for a specific bank at time t. Standardization is important to obtain an appropriate result by combining the different scale variables into one scale variable. Second, we have multiplied these components according to the weight that each one has on bank performance. Specifically, we have used the same weights that are used in Mahmud and Rahman (2020). Then, the weight assigned to each component and the weighted rating was calculated. Specifically, CAMEL’s parameters for each bank are calculated as follows:
where Sit is a standardized value of the CAMEL parameter of i th bank at time t, whereas the FPI of each bank for each year is calculated as follows:
where αj is the prescribed weight for banks i th at time t. CAit, AQit, MTit, ESit and LYit, are the CAMEL’ performance parameters for i th bank at time t.
This study analyzes the empirical determinants of bank performance by taking the FPI as the dependent variable, while bank-specific variables (overheads, reserves, bank size, deposits and operating efficiency), macroeconomic factors (GDP and Real interest rate) and financial market factors (marker capitalization and market concentration) act as independent variables. The independent variables are explained as follows:
3.3 Independent variables
3.3.1 Bank-specific variables
Overheads: can be defined as the cost of operating in a business, a low percentage indicates a positive performance and proves the effectiveness of banks’ performance when their costs decrease (Hassan and Bashir, 2003). It is calculated as follows:
Reserves: are retained earnings generated by the bank. They are calculated by taking the value of the natural logarithm reserves from the balance sheet of a certain bank for a particular year (Rashid and Jabeen, 2016). This calculation is as follows:
Bank size: is calculated in our study as the natural log of book value of total assets. Therefore, its expression is:
Deposits: are the primary sources of bank financing, and they are expected to be one of the most important ratios that affect the performance of banks (Rashid and Jabeen, 2016). They are calculated as follows:
Operating efficiency: displays how a business can efficiently use its assets and revenues. Therefore, it is calculated as the ratio of total expenditures that run a business operation to the total revenues obtained from the business (Almazari, 2014).
3.3.2 Macro indicators
GDP : is the value of a country’s goods and services produced within a certain period. It is often calculated at constant prices (Bikker and Hu, 2002). It is calculated as:
Inflation rate as the consumer price index.
Cellular use is measured by the cellular telephone subscriptions to a public cellular telephone service that offers voice communications. The variable is obtained from the World Bank. In this work, it is used as a proxy for the degree of expansion or prevalence of electronic banking in the different countries studied.
4. Results and discoveries
4.1 Empirical findings
The results of the mean tests show that there are no significant differences between I&CB during the period analyzed. Thus, our results are in contradiction with studies that state a better financial performance of IB during recession years.
This section examines the determinants of profitability by using several variables reported in Table 3. As can be observed, Table 3 provides descriptive statistics for all the variables under investigation for both I&CB. Most of the variables present similar means in both types of banks. Nevertheless, it is striking that the dependent variable (FPI) presents different signs depending on the type of bank. To analyze this different sign, an ANOVA analysis of variance was performed reporting that the difference is not statistically significant. Thus, this preliminary result suggests that the two types of banks do not present differences in the FPI. This finding is consistent with Wahab and Roslan’s (2021) study.
Descriptive statistics
| Conventional banks | Islamic banks | |||||
|---|---|---|---|---|---|---|
| Variables | Mean | SD | Mean | SD | ANOVA F statistic | Prob > F |
| FPI | 0.123 | 3.00 | −0.367 | 3.92 | 2.46 | 0.1170 |
| Overheads | −2.15 | 0.93 | −1.80 | 0.82 | ||
| Bank size | 16.07 | 1.38 | 16.41 | 1.17 | ||
| Retained earnings | 12.67 | 4.10 | 10.94 | 7.46 | ||
| Deposits | 7.09 | 3.01 | 12.00 | 42.09 | ||
| Operating efficiency | 0.936 | 0.73 | 0.716 | 0.560 | ||
| GDP (const.) | 25.60 | 1.05 | 25.89 | 1.07 | ||
| Inflation | 3.47 | 5.32 | 2.68 | 5.20 | ||
| Cellular | 138.64 | 44.14 | 152.18 | 43.71 | ||
Note:
This table provides (Mean) and the variability SD of the observations and an ANOVA analysis performed for FPI
To examine the influence of some of the determinants of bank performance, the following model has been estimated for I&CB separately:
where i is the bank, t is the time period and εit represents error terms.
The samples used to estimate the proposed model are data panels. The characteristics of the samples indicate that a GLS regression should be estimated due to the autocorrelation and heteroskedasticity found [1]. In addition, the estimation of fixed effects (FE), random effects (RE) and ordinary least squares (OLS) has also been carried out to give robustness to the results obtained.
Our findings are presented in two separate tables. Table 4 displays the results on determinants of conventional banks’ performances, while Table 5 shows the results on determinants of IB performances.
Determinants of conventional banks’ performances
| Panel effects | (1) | (2) | (3) | (4) |
|---|---|---|---|---|
| Pooled OLS | ||||
| Variables | RE | FE | GLS | |
| Overheads (OVHD) | −1.010*** (0.240) | −0.203(0.390) | −0.448 (0.344) | −0.487*** (0.115) |
| Bank size (SZE) | 0.0947 (0.155) | 0.740 (0.853) | 0.329 (0.257) | 0.110 (0.102) |
| Retained earnings (RSRV) | 0.442*** (0.0566) | 0.322*** (0.0676) | 0.344*** (0.0657) | 0.280*** (0.0478) |
| Deposit (DPST) | −0.600*** (0.0685) | −0.445*** (0.130) | −0.509*** (0.0907) | −0.490*** (0.0385) |
| Operating efficiency (OE) | −0.157 (0.229) | 0.485 (0.313) | 0.220 (0.281) | −0.179 (0.170) |
| GDP (const.) | 0.488*** (0.123) | 1.004 (2.835) | 0.363 (0.233) | 0.562*** (0.107) |
| Inflation (in) | 0.0212 (0.0291) | 0.0136 (0.0283) | 0.00983 (0.0289) | 0.0289* (0.0153) |
| Cellular (CE) | −0.00372 (0.00281) | −0.00255 (0.00541) | −0.00471 (0.00428) | −0.00411** (0.00209) |
| Constant | −17.09*** (2.773) | −39.52 (76.10) | −16.08*** (4.655) | −16.84*** (2.418) |
| Observations | 354 | 354 | 354 | 354 |
| R-squared | 0.636 | 0.480 | ||
| Number of banks | 59 | 59 | 59 | |
Notes:
Robust standard errors in parentheses;
***p < 0.01; **p < 0.05 and *p < 0.1.
The table displays the results of a study that investigated the financial performance of conventional banks in the MENA region using four different estimation methods: pooled OLS, panel effects, fixed effects and generalized least squares (GLS). The variables examined in this study include Overheads (OVHD), Bank size (SZE), Retained earnings (RSRV), Deposits (DPST), Operating efficiency (OE), GDP (const.), Inflation (IN) and Cellular (CE)
Breuch and Pagan Test for Inquiring Panel Effects
| Conventional Banks | Islamic Banks | ||
|---|---|---|---|
| H0: No Panel Effects | If H0 is rejected (p-value < 0.05) → there are panel data effect → Random or Fixed effects could be used | H0: No Panel Effects | If H0 is rejected (p-value < 0.05) → using a panel data model of fixed or random effects |
| Χ2(01) = 322.98 | Χ2(01) = 118.09 | ||
| p-value = 0.0000 | p-value = 0.0000 | ||
As observed in Table 4, our findings suggest that the financial performance of conventional banks in the MENA region is negatively affected by overhead costs. This outcome aligns with expectations, as overhead costs typically encompass nonrevenue-generating activities like administrative expenses, rent, utilities and salaries, which can significantly impact a bank’s profitability when not managed efficiently. These results are consistent with previous studies (Rashid and Jabeen, 2016; Serwadda, 2018). Furthermore, the MENA region’s reputation for high operational costs may exacerbate the negative impact of overhead costs on financial performance.
Our results also indicate that the size of a conventional bank does not have a significant impact on its financial performance. This finding is also at variance with the research by Zeitun (2012), which emphasized the substantial influence of bank size and the cost-to-income ratio on the performance of both I&CB. It differs as well from the findings of Muhindi and Ngaba (2018), which established a significant relationship between firm size and the financial performance of commercial banks in Kenya. This result suggests that a bank’s financial performance is not solely dependent on its size. Larger banks may possess more resources and economies of scale, potentially reducing costs and increasing profits, while smaller banks may be more agile and responsive to changing market conditions and customer needs.
In contrast, our results reveal a positive influence of retained earnings on financial performance, consistent with Nduati and Wepukhulu (2020). Their research demonstrated that retained earnings had a favorable and significant effect on a bank’s financial performance, as measured by ROA, ROE, and net interest margin. The significance of retained earnings can be explained by their use in profitable investments, improving capital positions and attracting investors.
Our findings also indicate a significant and adverse effect of deposits on conventional banks’ performances, suggesting a negative correlation between deposits and financial performance. This aligns with the study by Joseph and Adelegan (2023) on Nigerian banks, which found that deposits had an unfavorable impact on banks’ profitability during periods of low-interest rates. When interest rates were low, banks struggled to generate satisfactory returns on deposits, leading to decreased profitability. However, when interest rates were high, deposits had a positive impact on profitability, as banks could earn higher returns on their deposits.
Regarding operating efficiency, our results suggest that its impact on financial performance was not significant. This implies that further improvements in operating efficiency may not lead to substantial financial gains for banks. This finding contradicts the study by Rashid and Jabeen (2016), which identified operating efficiency, reserves and overheads as significant determinants of conventional banks’ performances.
Furthermore, our study examines the effect of macroeconomic factors on the financial performance of conventional banks. The results indicate a significant positive impact of GDP and inflation on financial performance in the MENA region. This implies that economic growth is a crucial factor in enhancing the financial performance of banks in this region. A growing economy often indicates a stable business environment that attracts more foreign investment and leads to increased deposits for banks. Similarly, the positive impact of inflation on financial performance can be attributed to higher interest rates, which result in increased interest income for banks. Additionally, inflation can stimulate a higher demand for credit, leading to increased lending and higher profits for banks. These findings align with studies conducted by Raiz and Maher (2013) and Quoc Trung (2021).
Regarding the variable named “Cellular,” our results indicate that the use of cellular phones and cellular banking services has a significant and negative impact on conventional banks’ financial performance. This suggests that increased competition and operational costs associated with the widespread use of cellular technology may have reduced banks’ profitability.
Table 5 presents the findings of our study regarding IB, highlighting that overhead costs exert a significant negative impact on financial performance, while bank size has a notable positive influence. The positive correlation between bank size and financial performance within IB suggests that larger institutions are generally better equipped to withstand economic challenges and are poised to capitalize on market growth opportunities. These outcomes align with prior research, such as that of Daly and Frikha (2015), who observed that larger IBs in Bahrain demonstrated superior profitability and risk management compared to smaller counterparts. Similarly, Zarrouk et al. (2016) found a positive association between bank size and financial performance among IB in the MENA region, with larger banks displaying higher profitability and asset quality.
Our research emphasizes the significant enhancement of IB’s performances through retained earnings. In essence, preserving earnings rather than disbursing dividends yields superior financial outcomes. Furthermore, aligning dividend policies with retained earnings can reduce share-price volatility, fostering market stability. This finding corroborates Al-Fayed’s study (2017) underscoring the critical role of prudent dividend decisions for IB to compete effectively in local and global deposit markets. Avoiding erratic dividend distributions that fail to signal market strength becomes crucial, as such practices could hinder capital acquisition and investor attraction, given their comparatively lower dividend yields compared to conventional banks.
Regarding the impact of other factors in IB, such as deposits, operating efficiency, inflation and cellular phone penetration, they are not statistically significant. The absence of a substantial impact of deposits on IB performances can be attributed to several factors. One plausible explanation is that IB operate within a distinct financial system compared to conventional banks, wherein deposits do not constitute the primary funding source. IB, instead, rely on diverse financing techniques such as leasing, profit sharing and asset-based financing, which offer a more stable and diversified funding source than deposits. This finding concurs with a study conducted by Rashid and Jabeen (2016), which noted that operating efficiency, reserves and overheads significantly influence conventional banks’ performances, while operating efficiency, deposits and market concentration significantly explain IB performances.
The absence of a notable impact of inflation on IB performances can also be explained by various factors. One plausible reason is that IB operates within a distinct financial system compared to conventional banks, where interest rates serve as the primary tool for managing inflation. Instead, IB rely on profit sharing and other noninterest-based financing methods, which may be less sensitive to fluctuations in inflation rates. This result contradicts the findings of Zeitun (2012), which highlighted the significant impact of GDP and inflation on banking performance. Additionally, the study revealed the substantial influence of bank size and the cost-to-income ratio on the performance of both I&CB.
In line with conventional banks, the Islamic bank’s results show that a strong GDP has a favorable effect on financial performance. The GDP is an indicator of economic health and stability, and a strong performance in this area typically suggests a stable economy with reduced risks. This can have a positive impact on the performance of I&CB since both types of banks face similar risk factors in the economy.
4.2 Theoretical and practical implications
The theoretical implications of the research paper lie in the distinct ethical principles that constitute the foundation of Islamic finance. The study underscores the profound impact of Quranic verses and prophetic hadiths addressing the prohibition of Riba, thereby emphasizing the ethical underpinning of Islamic finance. Illustrated in Surah Al-Baqarah (2:275–279) with the statement “But Allah permitted commerce, and He prohibited usury,” and echoed in the Hadith from Sahih Muslim (1598a) which states, “Allah’s Messenger (
) cursed the accepter of Riba and its payer, and one who records it, and the two witnesses, and he said: They are all equal”. This theoretical framework provides a distinctive perspective for scrutinizing economic activities and the operational landscape of IB, contributing to a more profound comprehension of the ethical considerations guiding their financial practices. The differentiation between positive principles, such as the payment of Zakat linked to real economic activity and negative principles, including the prohibition of Riba, condemnation of financing an illicit sector and prohibition of speculative “Gharar” illustrates the comprehensive ethical framework shaping Islamic financial institutions (Daly and Frikha, 2017).
On a practical level, the study underscores the significance of efficient overhead cost management for conventional banks, particularly in the context of a rapidly evolving digital banking environment. The call for adaptation and innovation in operational strategies aligns with the broader principles of efficiency and effectiveness emphasized in Islamic finance. The point of conventional banks further raises the issue of operational efficiency and the inevitable increase in overhead cost management. To be competitive with the advancing technology and financial governance, traditional banks must simplify their operations by adopting the technology and will regulate themselves in a prudent and financially aware manner. In addition, the retained earnings plan is sought by investors as another essential step for continuous growth.
The ethical opposition to Riba is poised to have extensive social implications, influencing market stability, commercial and economic impact and contributing to responsible banking practices within the Islamic banking sector. The study suggests that adherence to these sacred principles not only aligns with ethical considerations but also fosters social responsibility within Islamic banking institutions. This holds significance for broader societal and economic impacts, as responsible banking practices contribute to sustainable and equitable economic development.
The size of IB positively influences their financial performance, suggesting that larger banks are more adept at navigating market fluctuations in the MENA region. This relationship underscores the importance of scale in enhancing the competitiveness and sustainability of IB. Policymakers, regulators and industry stakeholders should, therefore, encourage the growth and expansion of IB to enhance their performance and contribution to the financial landscape. Additionally, consolidation or strategic partnerships could be advantageous for IB, as they can improve their size and resilience to economic changes, enabling them to capitalize on economies of scale. Prioritizing growth and scaling strategies may have the potential to fortify the Islamic banking sector and facilitate sustainable economic development and financial inclusion in the MENA region.
Both conventional and IB in the MENA region should explore digital solutions and technologies to enhance their popularity, thereby creating significant opportunities for industry growth. Additionally, it is essential for both types of banks to incorporate religious-based ethical standards along with educational initiatives to foster their development. These consequences fundamentally reinforce the objective of insightful planning and refining strategies to brave the shifts and turn in the panorama of the banking industry.
In essence, the theoretical, practical and social implications of the study surpass the narrow focus on financial performance, resonating with the broader societal, economic and educational landscape within the Islamic banking sector. The integration of ethical principles not only reinforces the unique identity of Islamic finance but also positions it as a model for responsible and sustainable banking practices in the MENA region and beyond.
5. Conclusion
This study provides valuable insights into the financial performance of I&CB in the MENA region. Our analysis has illuminated various factors influencing their performance, emphasizing the significance of efficient overhead cost management for conventional banks, particularly in the evolving digital banking landscape. Therefore, to ensure profitability, these conventional institutions must prioritize strategies that improve operational efficiency. Moreover, the study challenges the conventional belief that the size of a bank alone guarantees financial success, highlighting the potential for smaller, more agile banks to thrive. It also underscores the positive impact of retained earnings on the financial performance of both bank types, suggesting potential benefits in terms of market stability when aligning dividend policies with retained earnings. Deposit management is identified as a crucial consideration for both conventional and IB, with the former needing strategies to retain deposits during periods of low interest rates and the latter encouraged to diversify financing techniques due to their unique funding sources. Additionally, the study suggests that further enhancements in operating efficiency may not yield significant financial gains, prompting exploration into diversified growth avenues. Moreover, the study reiterates the positive correlation between GDP growth and banks’ financial performances, emphasizing the central role of economic health in shaping profitability. This provides insights for MENA banks and strategic direction for governments and industry stakeholders. Quranic verses emphasize ethical conduct, fairness and justice in economic transactions, providing a moral framework for financial activities.
While this study offers valuable insights, it is essential to acknowledge its limitations. The research focuses on a specific region (MENA) and may not be universally applicable to other geographical areas or banking systems. The study’s findings are based on historical data and might not fully reflect current or future market conditions. Additionally, the choice of variables and methodology may introduce bias or limitations, as with any empirical study. Future research could benefit from a broader geographical scope and more up-to-date data to further enhance the generalizability of the findings and address these limitations.
Determinants of Islamic banks’ performances
| (1) | (2) | (3) | (4) | |
|---|---|---|---|---|
| Pooled OLS | ||||
| Variables | FE | RE | GLS | |
| Overheads (OVHD) | −0.410 (0.405) | −1.083 (0.718) | −1.428* (0.764) | −0.749** (0.300) |
| Bank size (SZE) | 0.414 (0.420) | −3.304 (2.064) | 0.0145 (0.845) | 0.881*** (0.271) |
| Retained earnings (RSRV) | 0.108** (0.0486) | 0.232*** (0.0783) | 0.190*** (0.0549) | 0.124*** (0.0353) |
| Deposit (DPST) | −0.00744** (0.00310) | −0.00652** (0.00281) | −0.00339 (0.00227) | −0.0121 (0.00833) |
| Operating efficiency (OE) | −1.010 (0.648) | 1.812 (1.291) | −0.159 (1.096) | −0.550 (0.511) |
| GDP (const.) | 0.606 (0.400) | −10.82** (4.660) | 0.424 (0.753) | 0.581* (0.308) |
| Inflation (IN) | −0.185*** (0.0653) | −0.0503 (0.0665) | 0.0100 (0.0493) | −0.0107 (0.0376) |
| Cellular (CE) | −0.00300 (0.0112) | −0.000124 (0.0196) | 0.0154 (0.0129) | −0.00338 (0.00532) |
| Constant | −22.94** (10.05) | 328.4** (133.2) | −18.39 (20.63) | −31.68*** (6.908) |
| Observations | 149 | 149 | 149 | 149 |
| R-squared | 0.245 | 0.157 | ||
| Number of banks | 25 | 25 | 25 | |
Notes
: Robust standard errors in parentheses;
***p < 0.01, **p < 0.05 and *p < 0.1.
The table displays the results of a study that investigated the financial performance of Islamic banks in the MENA region using four different estimation methods: pooled OLS, panel effects, fixed effects and generalized least squares (GLS). The variables examined in this study include Overheads (OVHD), Bank size (SZE), Retained earnings (RSRV), Deposits (DPST), Operating efficiency (OE), GDP (const.), Inflation (IN) and Cellular (CE)
Note
The results of the Wooldridge autocorrelation test and the Wald heteroskedasticity test are found in Appendix.
References
Further reading
Appendix
Hausman Test - Choice between Fixed and Random Effects
| Conventional Banks | Islamic Banks | ||
|---|---|---|---|
| H0: Difference in coefficients not systematic | If H0 is rejected (p-value < 0.05) → the fixed effects model should be use | H0: Difference in coefficients not systematic | If H0 is rejected (p-value < 0.05) → the fixed effects model should be use |
| χ2(6) = 28.58 | χ2(6) = 18.06 | ||
| p-value = 0.0001 | p-value = 0.0061 | ||
Wooldridge Test for Serial Correlation
| Conventional Banks | Islamic Banks | ||
|---|---|---|---|
| H0: No first-order autocorrelation | If H0 is rejected (p-value < 0.05) → there is serial correlation | H0: No first-order autocorrelation | If H0 is rejected (p-value < 0.05) → there is serial correlation |
| F (1, 57) = 18.851 | F (1, 25) = 9.412 | ||
| p-value = 0.0001 | p-value = 0.0051 | ||
Modified Wald Test for Group Wise Heteroskedasticity
| Conventional Banks | Islamic Banks | ||
|---|---|---|---|
| H0: σi2=σ for all i | If H0 is rejected (p-value < 0.05) → there is heteroskedasticity | H0: σi2 = σ for all i | If H0 is rejected (p-value < 0.05) → there is heteroskedasticity |
| χ2(58) = 24998.38 | χ2(26) = 7755.73 | ||
| p-value = 0.0000 | p-value = 0.0000 | ||
CAMELS Parameters
| CAMELS | RATIO | MEANING |
|---|---|---|
| C Capital adequacy | shareholders equity/total assets | It means the bank's capital adequacy and its ability to deal with losses and face risks. This ratio indicates whether the bank needs external financing to support the capital in the event of its decline |
| A Asset quality | Non-performing loan/total assets | It is the amount of risky and non-performing assets owned by the bank and is determined as a percentage of total assets |
| M Management soundness | Cost to income | It is the management's ability to achieve the highest income at the lowest costs, and this is an indication of the management's efficiency in dealing with conditions and risk factors |
| E Earnings | ROA | This ratio is the profitability of the bank, as it is the bank's ability to regularly earn income from its activities |
| L Liquidity | Loan to deposit | It is the ability of the bank to meet its obligations as they arise |
