Prof. Ibrahim Elsiddig Ahmed Ibrahim has been a Professor at Ajman University since May 2022. He earned his Ph.D. in Accounting and Finance from the University of Khartoum in 2003. With more than two decades of academic experience, he has served as an Associate Professor and Assistant Professor at Ajman University and Al Ghurair University in Dubai. His research interests include financial analysis, performance evaluation, risk analysis, corporate governance, and intellectual capital measurement.
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Purpose: This study’s objective is to examine credit risk management's effect on the financial performance of the Sudanese banking sector. Design/Methodology/Approach: Every bank’s financial report for a 10-year period, from 2006 to 2015 had been employed for the study. To estimate the model, the panel regression method was used. For performance indicators, ROE (Return on Equity) was used. Meanwhile, for credit risk management indicators, NPL (Non-Performing Loans) and CAR (Capital Adequacy Ratio) were utilized. Findings: The results showed that the profitability of Sudanese banks is significantly influenced by credit risk management. The evidence shows that 57% of profitability in banks is affected by the change in capital adequacy ratio and non-performing loans. The study also shows there is a positive relationship between the banks’ financial performance and capital adequacy ratio, but the correlation is not significant. Furthermore, the correlation between the banks’ financial performance and non-performing loans is significant but negative. Practical Implications: The percentage of the impact of NPL (non-performing loans) and CAR (capital adequacy ratio) on the banks’ financial performance is 57%; which means the profitability of banks is impacted by the changes in NPL and CAR. Originality/Value: This study helps filling the aperture in the empirical evidence of how credit risk management impacts the bank’s financial performance process in Sudan.
Purpose: This study’s objective is to examine the credit risk management's effect on the financial performance of the Sudanese banking sector. Design/Methodology/Approach: Every bank’s financial reports for a 10-year period, from 2006 to 2015 been employed for the study. To estimate the model, the panel regression method was used. For performance indicators, ROE (Return on Equity) was used. Meanwhile, for credit risk management indicators, NPL (Non-Performing Loans) and CAR (Capital Adequacy Ratio) were utilized. Findings: The results showed that credit risk management significantly influences the profitability of Sudanese banks. The evidence shows that 57% of profitability in banks is affected by the change in capital adequacy ratio and non-performing loans. The study also shows there is a positive relationship between the banks’ financial performance and capital adequacy ratio, but the correlation is not significant. Furthermore, the correlation between the banks’ financial performance and non-performing loans is significant but negative. Practical Implications: The percentage of the impact of NPL (non-performing loans) and CAR (capital adequacy ratio) on the banks’ financial performance is 57%; which means the profitability of banks is impacted by the changes in NPL and CAR. Originality/Value: This study helps fill the aperture in the empirical evidence of how credit risk management impacts the bank’s financial performance process in Sudan.
This study aims to suggest a measurement of intellectual capital (IC) based on its contribution to generating additional returns that result from efficient and effective use of investments in IC as compared to the investment in other assets. The study develops a derivative model composed of 17 equations to measure the value of IC through the contribution approach measured by the participation of IC in generating revenues (Eq. 16) and explains how additional investment in IC will lead to additional earnings. The study constructs a relationship between the value of the investment in IC and its effectiveness in generating revenues and profits of the firm. It also considers the size and leverage as control variables to reduce the impact of exogenous factors. To investigate the contribution of IC, the study analyzed the financial data of all 21 UAE national banks over a 5-year period (2015–2019). The model determines the optimal investment in IC that results in the maximum value of profits of a bank. The main findings of the study are a significant positive relationship between the IC contribution and investment in IC (0.498), IC contribution, and earnings (0.219); IC contribution has a significant negative relationship with the bank size (−0.238); and a significant positive relationship between the increase in earnings and an increase in investment in IC (0.171). The model adds a new body of knowledge to the literature and helps practitioners to assess the contribution of the IC and optimal investment in IC. The model measures IC based on the bank’s annual performance. In the future, research may be extended to other sectors and contexts. Keywords Intellectual capital · IC performance approach · IC derivative model ·
Purpose – This study aims at investigating banks’ compliance with the disclosure requirements of Basel III in two emerging market economies, namely, the United Arab Emirates (UAE) and India. This study also examines the impact of economic factors on the extent of disclosures. Design/methodology/approach – The authors compare the Basel disclosure practices between UAE and Indian listed banks and have used panel data regression models to investigate the compliance and level of reporting based on three market variables, namely, size, leverage, and profitability of listed banks. Findings – After examining Basel reporting for each of the three categories of independent factors, size was found to be the predominant factor influencing the Basel disclosures, followed by profitability and degree of financial leverage. It is prudent for all the banks irrespective of size to capitalize on themselves with an intent to tide over the frequent economic crises and prevent every economic crisis from becoming a full-blown financial crisis. Practical implications – The findings suggest that there is an urgent need for a high level of concerted action in the context of listed banks in the selected emerging market nations to direct more resources to ensure full compliance with Basel III. The findings inform practitioners in emerging countries of compliance and plan expanded future applications. Investors should consider the BASEL compliance level of Banks before parking their funds in the bank’s stocks. The banks having a higher degree of compliance are expected to be safer than their counterparts having lower Basel compliance. Originality/value – Many previous studies have examined the implementation of Basel III in general. This study is specific in assessing compliance with disclosure requirements as prescribed by Pillar III of the Basel norms. To the best of the authors’ knowledge, this is the first research to compare market discipline in emerging markets. Existing studies have either assessed the level of compliance in one individual or similar types of markets. However, this study made a pioneering attempt to compare two different countries in the same category (emerging markets).
This essay examines the third increase in non-performing loans (NPLs) in the Arab World, which the COVID-19 epidemic may have contributed to. This increase follows two previous waves that occurred in 1990 and after 2008. The primary aim is to analyze bank lending behavior, particularly examining the influence of firm-specific determinants on banks' lending activities and the impact of NPLs on this behavior. Utilizing secondary data from 2016 to 2020, this research focuses on the top ten national banks in the Arab region. The methodology incorporates panel data derived from audited financial statements and employs OLS regression (Pooled) for analysis. The findings reveal a significant negative impact of NPLs and capital adequacy ratios on bank lending behavior, while bank size and deposit growth positively influence lending activities. Additionally, the study notes an insignificant relationship between profitability, equity as a percentage of total assets, and lending behavior. These results provide practical insights for banking sector decision-makers, emphasizing the management of NPLs through maintaining adequate capital, enhancing deposits, and increasing bank assets. From a social perspective, the study suggests that banks should prioritize lending to investors likely to fulfil their obligations, potentially limiting credit availability for smaller entities and individuals without guarantees. This approach aims to mitigate the risks associated with NPLs. This work's originality lies in its concentration on a condensed sample that accounts for more than 70% of the banking resources in the Arab region, making it a significant contribution to applied research in this area that stands out for its reliance on pre-existing data.
Banking risk measurement and management remain one of many challenges for managers and policymakers. This study contributes to the banking literature and practice in two ways by (a) proposing a risk ranking index based on the Mahalanobis Distance (MD) between a multidimensional point representing a bank’s risk measures and the corresponding critical ratios set by the banking authorities and (b) determining the relative importance of a bank’s risk ratios in affecting its financial standing using an Adaptive Neuro-Fuzzy Inference System. In this study, ten financial ratios representing five risk areas were considered, namely: Capital Adequacy, Credit, Liquidity, Earning Quality, and Operational risk. Data from 45 Gulf banks for the period 2016–2020 was used to develop the model. Our findings indicate that a bank is in a sound risk position at the 99%, 95%, and 90% confidence level if its Mahalanobis distance exceeds 4.82, 4.28, and 4.0, respectively. The maximum distance computed for the banks in this study was 9.31; only five out of the forty-five banks were below the 4.82 and one below the 4.28 and 4.0 thresholds at 3.96. Sensitivity analysis of the risks indicated that the Net Interest Margin is the most significant factor in explaining variations in a bank’s risk position, followed by Capital Adequacy Ratio, Common Equity Tier1, and Tier1 Equity in order. The remaining financial ratios: Non-Performing Loans, Equity Leverage, Cost Income Ratio, Loans to Total Assets, and Loans to Deposits have the least influence in the order given; the Provisional Loans Ratio appears to have no influence.
Purpose – This study aims at investigating banks’ compliance with the disclosure requirements of Basel III in two emerging market economies, namely, the United Arab Emirates (UAE) and India. This study also examines the impact of economic factors on the extent of disclosures. Design/methodology/approach – The authors compare the Basel disclosure practices between UAE and Indian listed banks and have used panel data regression models to investigate the compliance and level of reporting based on three market variables, namely, size, leverage and profitability of listed banks. Findings – After examining Basel reporting for each of three categories of independent factors, size was found to be the predominant factor influencing the Basel disclosures, followed by profitability and degree of financial leverage. It is prudent for all the banks irrespective of size to capitalize on themselves with an intent to tide over the frequent economic crises and prevent every economic crisis from becoming a full-blown financial crisis. Practical implications – The findings suggest that there is an urgent need for a high level of concerted action in the context of listed banks in the selected emerging market nations to direct more resources to ensure full compliance with Basel III. The findings inform practitioners in emerging countries of compliance and plan expanded future applications. Investors should consider the BASEL compliance level of Banks before parking their funds in the bank’s stocks. The banks having a higher degree of compliance are expected to be safer than their counterparts having lower Basel compliance. Originality/value – Many previous studies have examined the implementation of Basel III in general. This study is specific in assessing the compliance with disclosure requirements as prescribed by Pillar III of the Basel norms. To the best of the authors’ knowledge, this is the first research to compare market discipline in emerging markets. Existing studies have either assessed the level of compliance in one individual or similar types of markets. However, this study made a pioneering attempt to compare two different countries in the same category (emerging markets).
This study examines the determinants of capital structure in family owned businesses in the GCC countries, focusing on internal company characteristics and their impact on leverage decisions. It analyzes panel data from 99 family owned companies from the LSEG database (2015-2023), using fixed effects regression and IV 2SLS approaches to address potential endogeneity. The findings reveal that profitability and sales growth negatively impact leverage, supporting the pecking order theory, while asset tangibility and firm size positively influence leverage. Liquidity, market-to-book value, and firm age become significant with different effects when addressing endogeneity. The interest rate negatively predicts leverage, whereas regulatory quality contributes to an increase in leverage size. This study contributes to the limited research on capital structure determinants in GCC family businesses by providing insights into how family ownership influences financing decisions in Gulf countries and examining the relevance of capital structure theories in this context. The findings offer valuable insights for family business owners, managers, and policymakers in the GCC, aiding effective financial management, succession planning, and the long-term sustainability of family businesses.
The rapid advancement of Blockchain technology has significantly benefited banks with more efficiency, highly secured activities, compliance, fraud prevention, and risk control. All previous studies focused on stakeholders’ perceptions and ignored measuring the value of blockchain adoption. This study addresses this gap by quantifying and rating blockchain’s impact on reducing banking transaction costs. The data has been collected from 17 of 20 United Arab Emirates national banks over 2017–2023 and analyzed using the random forest method to assess the association between blockchain adoption and four transaction cost elements. The random forest technique accurately quantifies and classifies blockchain’s role in cost reduction. The findings indicate that blockchain adoption significantly reduces processing, transfer, and fraud costs. This study has a visible practical and theoretical contribution as it shifts focus to quantifying blockchain’s impact, providing useful insights for managers, and suggesting future research across different sectors and countries.
This study aims to rate the impact of the three major risks (credit, capital adequacy, and liquidity) on three financial performance measures (return on equity (ROE), earnings per share (EPS), and price-earnings ratio (PER)). This study stands out as one of the few in its field, and the only one focusing on banks in the Middle East and Africa, to employ the adaptive neural network-based fuzzy inference system (ANFIS) that combines neural networks and fuzzy logic systems. The significance of this study lies in its comprehensive coverage of major risks and performance variables and its application of highly technical, sophisticated, and precise AI techniques (ANFIS). The main findings indicate that credit risk, as measured by the non-performing loans (NPL), has a significant impact on both ROE and EPS. Liquidity risk comes second in importance for ROE and EPS, with the loan-deposit ratio (LDR) being the dominant component. In contrast, liquidity risk is the most significant determinant of PER, followed by capital adequacy. Our results also show that CAR, LDR, and NPL are the most significant risk components of capital adequacy, liquidity, and credit risks, respectively. The study contributes to business knowledge by applying the ANFIS technique as an accurate predictor of risk rating. Future research will explore the relationship between risks and macroeconomic indicators and differences among countries.