Search Results (403)

This paper measures the post-treatment effects of Central Bank Digital Currencies (CBDCs) on mobile money and outstanding loans from commercial banks as a percentage of the GDP in Nigeria and the Bahamas, respectively, from the perspective of financial inclusion. The literature on the topic has primarily focused on the technological specifications of CBDCs and their potential future implementation. This article addresses a gap in the empirical literature by examining the effects of CBDCs. To this end, a Synthetic Control Method (SCM) is applied to the Bahamas (SandDollar) and Nigeria (eNaira) to construct a counterfactual scenario and assess the impact of CBDCs on mobile money and commercial bank loans. Nigeria’s mobile money transactions as a percentage of the GDP increased significantly compared to the synthetic control group, suggesting a notable positive effect of the eNaira. Conversely, in the Bahamas, actual performance fell below the synthetic control, implying that SandDollar may have contributed to a decline in outstanding loans. These results suggest that CBDCs could pose a “deposit substitution risk” for commercial banks. However, they may also enhance the performance of other Fintech tools, as observed in the case of mobile money. As CBDC implementations worldwide remain in their early stages, their long-term effects require further analysis. Full article

The importance of non-performing loans (NPLs) for the stability of financial sectors is difficult to overestimate. The NPL level depends on numerous factors; this study’s goal is to determine the impact of macroeconomic factors on NPLs with the mediation effect of foreign, saving and social factors in Kazakhstan’s banking sector. To determine the affecting factors, the authors performed a systematic literature review. To determine the dependencies between constructs, the Partial Least Squares Structural Equation Modeling (PLS-SEM) method was used. Macroeconomic factors’ direct effect on non-performing loans (NPLs) was examined; a significant negative dependence was determined. The mediation effect of foreign, saving, and social factors was investigated. Foreign factors have a mediation effect, strengthening the dependence between macro factors and NPLs. Nevertheless, they do not have a mediating effect; moreover, they balance and make the effect of macro factors on NPLs statistically insignificant. These findings allow policy-makers to stabilize the situation on NPLs in the financial markets of developing countries like Kazakhstan by directly influencing not only the financial sector but also other sectors of the national economy. Full article

This study examines the long-term financial sustainability of commercial banks, emphasizing the crucial role of credit risk management. Given that the core function of credit creation inherently exposes banks to credit risk, this analysis evaluates how five key bank-specific risk variables, namely expected credit losses (ECL_BS), impairment gains or losses (ECL_IS), non-performing loans (NPLs), common equity tier 1 capital (CET1), and leverage (LEV) affect long-term financial sustainability. Applying a panel error correction model on data from listed South African banks spanning 2006 to 2023, the study reveals a stable long-term relationship, with approximately 74% of short-term deviations corrected over time, indicating convergence towards equilibrium. By taking into account the significance of major exogeneous shocks such as the 2009–2010 global financial crisis and the COVID-19 pandemic, as well as regulatory framework changes, the results reveal persistent relationships between credit risk factors and banks’ long-term financial sustainability in both short and long horizons. Notably, expected credit losses, and impairment gains and losses exert significant negative influence on long-term financial sustainability, while higher CET1 and NPLs exhibit positive effects. The study findings are framed within four complementary theoretical perspectives—the resource-based view, institutional theory, industrial organisation, and the dynamic capabilities framework—highlighting the multidimensional drivers of financial resilience. Thus, the study’s originality lies in its integrated approach to assessing credit risk, offering a holistic model for evaluating its influence on long-term financial sustainability. This integrated framework provides valuable, actionable insights for financial regulators, bank executives, policymakers, and banking practitioners committed to strengthening credit risk frameworks and aligning banking sector stability with broader sustainable development goals. Full article

Bank operations are contingent upon investor confidence, particularly during periods of economic distress. If investor confidence drops, a bank faces difficulties obtaining money, higher borrowing costs, and lower stock values. Non-performing loans (NPLs) potentially jeopardize a bank’s long-term viability and short-term profitability, and investors are naturally wary of institutions that pose a high credit risk. The purpose of the study was to explore how non-performing loans influence investor confidence in banks. A purposive sampling technique was used to identify 253 New York Stock Exchange banks in the Thomson Reuters Eikon DataStream that satisfied all the inclusion and exclusion selection criteria. The Common Correlated Effects Mean Group (CCEMG) and Generalized Method of Moments (GMM) models were used to analyze the data, providing insight into the relationship between the variables. The study discovered that NPLs had a negative and significant influence on price–earnings (P/E) and price-to-book value (P/B) ratios. Furthermore, the bank’s age was found to have a positive and significant relationship with the P/E and P/B ratio. The moderating relationship between NPLs and bank age was found to have a negative and significant influence on price–earnings (P/E) and price-to-book value (P/B) ratios. The findings underscore the importance of asset quality and institutional reputation in influencing market perceptions. Bank managers should focus on managing non-performing loans effectively and leveraging institutional credibility to sustain investor confidence, particularly during financial distress. Full article

The ability of the agriculture sector, which is exposed to climate hazards, to cope with climate challenges and to strive in spite of them, is conceptualized as the resilience of agriculture. In enhancing climate-resilient agriculture, the cash reserve ratio (CRR) is generally perceived to serve two crucial functions: first, encouraging banks to allocate credit to agriculturalists for climate-resilient agricultural practices; second, enhancing agriculturalists’ ability to sustain agricultural output growth in spite of climate crises. In light of this, we conducted an ex post evaluation of the effect of the currently in-use CRR on bank loans to climate-challenged Nigeria’s agriculture sector for climate-resilient agricultural practices. Additionally, this study investigates the CRR’s impact(s) on agricultural output growth amidst climate challenges. Other additional independent variables include monetary policy rate, government capital expenditures on agriculture, and government recurrent expenditures on agriculture, as well as temperature, precipitation, and the renewable energy supply. Using annual data from 1990 to 2022, the results from an autoregressive, distributed lag approach suggest that the standard CRR stipulated by the Central Bank of Nigeria in the present era of climate change cannot entirely sustain climate-resilient agriculture, evident in the present study’s discoveries on its inability to perform its two major functions (credit and growth) in enhancing agricultural resilience. These findings highlight the need for the green differentiation of the CRR to ensure its effective utilization in enhancing climate resilience. Full article

This study aims to analyze the determinants of bank profitability in Angola by employing panel data econometric models, specifically, the Generalized Method of Moments (GMM), to assess the impact of internal and external factors on the financial indicators ROE, ROA, and NIM for the period 2016 to 2023. The results reveal that credit risk, operational efficiency, and liquidity are critical determinants of banking performance. Effective credit risk management and cost optimization are essential for the sector’s stability. Banking concentration presents mixed effects, enhancing net interest income while potentially undermining efficiency. Economic growth supports profitability, whereas inflation exerts a negative influence. The COVID-19 pandemic worsened asset quality, increased credit risk, and led to a rise in non-performing loans and provisions. Reforms implemented by the National Bank of Angola have contributed to strengthening the banking system’s resilience through restructuring and regulatory improvements. The rise of digitalization and fintech presents opportunities to enhance financial inclusion and efficiency, although their success relies on advancing financial literacy. This study contributes to the literature by providing updated empirical evidence on the factors influencing bank profitability within an emerging economy’s distinctive institutional and economic context. Full article

The current study examines the application of advanced machine learning (ML) techniques for forecasting credit risk in Islamic (participation) and traditional banks in the United Kingdom in 2010–2023. Leveraging an equally weighted panel dataset and guided by robust empirical literature, we integrate structural econometric modeling—i.e., the stochastic frontier approach (SFA) to measuring the Lerner index of market power—with current best-practice tree-based ML algorithms (CatBoost, XGBoost, LightGBM, and Random Forest) to predict non-performing loans (NPLs). The results show that bank-level financial performance measures, particularly loan ratio, profitability, and market power, outperform macroeconomic factors in forecasting credit risk. Among the models tested, CatBoost was more accurate and explainable, as confirmed by SHAP-based explainability analysis. The implications of the research have practical applications for risk managers, regulators, and policymakers in terms of valuing the explanatory power of explainable AI tools to enhance financial oversight and decision-making in post-crisis UK banking. Full article

This study investigates the relationship between disclosures related to Sustainable Development Goal 7 (SDG 7) and the financial profitability of Romanian commercial banks during the 2017–2023 period. Using an unbalanced panel dataset of 17 banks and applying fixed-effects regression models, the paper examines how transparency around energy-related sustainability practices influences various dimensions of bank profitability: recurring earning power (REP), loan yield (LY), return on assets (ROA), and return on equity (ROE). Macroeconomic energy indicators, such as the energy intensity level of primary energy (EnInt) and renewable energy consumption (REnC), are also controlled for. The findings indicate that SDG 7.1 disclosures are negatively associated with all profitability measures, except for LY, suggesting potential short-term trade-offs between sustainability transparency and financial outcomes. In contrast, SDG 7.2 disclosures positively impact REP, ROA, and ROE, underscoring the financial relevance of renewable energy financing. SDG 7.a disclosures show no significant relationship with profitability, indicating limited operational involvement in global energy cooperation. Additionally, higher energy intensity negatively affects REP and LY, supporting existing evidence that energy efficiency improves banking performance. These findings have implications for banking strategy, emphasizing the need to align sustainability disclosures with business priorities while recognizing the long-term benefits of green finance and energy efficiency. Full article

Over the past decade, the rapid growth of supply chain finance (SCF) in developing countries has made it a key profit driver for commercial banks and financial firms. In parallel, financial risk control in SCF has attracted more and more attention from financial service providers and has gained research momentum in recent years. This study analyzes the contagion mechanism of SCF-related risks faced by commercial banks through examining SCF network topology. First, this study uses complex network theory to integrate an SEIR epidemic model (Susceptible–Exposed–Infectious–Recovered) into financial risk management. The model simulates how financial risks spread in supply chain finance (SCF) under banks’ strategic, tactical, or operational interventions. Then, some key points for financial risk control from the perspective of commercial banks are obtained by investigating the risk stability threshold of the financial network of SCF and its stability. Numerical simulations show that effective interventions—such as strengthening loan guarantees to reduce the number of exposed firms—significantly curb risk transmission by restricting its scope and shortening its duration. This research provides commercial banks with a quantitative framework to analyze risk propagation and actionable strategies to optimize SCF risk control, enhancing financial system stability and offering practical guidance for preventing systemic risks. Full article

This study explores how geographical factors shape El Salvador’s banking sector, particularly focusing on regional disparities, urbanization, and vulnerability to natural disasters affecting access to financial services. By employing a mixed-methods approach that combines quantitative data and qualitative interviews, the research analyzes how these geographical challenges impact financial inclusion and banking development. Data from the Central Reserve Bank of El Salvador and financial institutions is examined alongside Geographic Information Systems (GISs) to illustrate the spatial distribution of banking services. Interviews with stakeholders, including bank representatives and clients from urban and rural areas, reveal a significant urban–rural divide, with approximately 75% of bank branches and 80% of ATMs situated in urban centers, particularly in San Salvador. Rural areas face limited access to formal banking due to challenging topography and inadequate infrastructure, leading to increased financial exclusion and reliance on informal systems. Natural disasters further disrupt banking infrastructure and heighten the need for emergency loans. While urbanization has spurred financial growth, it has also resulted in informal settlements with restricted access to formal services. As its main contribution, this study provides one of the first in-depth, geographically grounded analyses of financial exclusion in El Salvador, offering original insights into how spatial inequalities and disaster vulnerability intersect to shape banking access and economic participation. The study calls for a more inclusive banking sector, recommending mobile and digital banking expansion, agent banking in underserved areas, and improved disaster risk management to enhance economic participation across all regions. Full article

This paper assesses whether fintech mortgage lenders align pricing with borrower risk using conforming 30-year mortgages (2012–2020). We estimate default probabilities using machine learning (logit, random forest, gradient boosting, LightGBM, XGBoost), finding that non-fintech lenders achieve the highest predictive accuracy (AUC = 0.860), followed closely by banks (0.857), with fintech lenders trailing (0.852). In pricing analysis, banks adjust the origination rates most sharply with borrower risk (7.20 basis points per percentage-point increase in default probability) compared to fintech (4.18 bp) and non-fintech lenders (5.43 bp). Fintechs underprice 32% of high-risk loans, highlighting limited incentive alignment under GSE securitization structures. Expanding the allowable alternative data and modest risk-retention policies could enhance fintechs’ analytical effectiveness in mortgage markets. Full article

The Middle East and North Africa (MENA) region has faced challenges like political instability and economic fluctuations, which have impacted non-performing loans (NPL) levels. At the same time, over the years, reforms and regulations have encouraged stronger board structures to enhance corporate governance and improve risk management. The purpose of this paper is to investigate how board characteristics affect non-performing in the MENA region. Board characteristics shape governance quality, which influences risk management and reduces banks’ risk-taking behaviours. Hence, effective governance can reduce non-performing loans by improving oversight and credit decisions. To this end, we used a sample of 70 banks operating in 12 countries in the MENA region from 2010 to 2022. The System Generalized Method of Moments (SGMM) was employed as an empirical technique. To benefit from a comparative analysis, we divided the entire sample into two subsamples. The first subsample covers six Gulf Cooperation Council (GCC) countries with 42 banks. The second subsample is also relative to six non-Gulf Cooperation Council (non-GCC) countries with 28 banks. The empirical findings indicate that the presence of independent board members, a higher number of female board members, board remuneration, and the board index decrease NPLs across all regions, including MENA, GCC, and non-GCC. However, we found that board size, tenure, and duality increase NPLs. The results of this paper are beneficial for both policymakers and bankers, as they provide insights into how governance through board characteristics influences credit risk. These results support better decision-making in board appointments and governance practices to improve risk management and reduce non-performing loans. Full article

There is an ongoing debate about the role of income diversification in enhancing bank stability within the financial services industry in Europe. Some advocate for diversification, while others argue that its importance should not be overstated. Some financial institutions are encouraged to focus on their traditional investments instead of income diversification, while others suggest that income diversification can stabilize or destabilize, depending on the regulatory environment. These conflicting results indicate a lack of clear evidence regarding the effectiveness of income diversification. Therefore, this paper aims to study the impact of income diversification on bank stability and enhance the predictive performance of bank stability by analyzing the period from 2000 to 2021 using a sample from 26 European countries, based on aggregate bank data. It employs a hybrid method that combines econometric techniques, specifically the generalized method of moments and a fixed-effects model, with machine-learning algorithms such as Random Forest and Support Vector Machine. These methods are applied to enhance the reliability and predictive power of the analysis by addressing the problem of endogeneity (via generalized method of moments) and capturing non-linearities, interactions, and high-dimensional patterns (via machine learning). The econometric findings reveal that income diversification can reduce non-performing loans, improve bank solvency, and enhance the Z-score, indicating the significant role of income diversification in improving bank stability. Conversely, the results also show that the machine-learning algorithms used play a crucial role in enhancing the predictive performance of bank stability. Full article

Over the past decade, the debate on the microeconomic effects of financial inclusion has intensified, with a growing body of research exploring how access to financial services impacts banks’ behaviors. Studying the effect of financial inclusion on bank risk is crucial because it helps understand how expanding access to financial services influences exposure to bank risks. This study explores the impact of financial inclusion on credit risk, measured by non-performing loans (NPLs), and liquidity risk measured by the loan-to-deposit (LTD) ratio in the Middle East and North Africa (MENA) region. The analysis is based on a sample of 74 banks observed between 2010 and 2021, and uses the System Generalized Method of Moments (SGMM). To conduct a comparative analysis, the whole sample is divided into two groups: the first includes GCC countries, while the second consists of non-Gulf Cooperation Council countries (NGCC). This sensitivity analysis was justified by several economic, financial, social, and regulatory differences between these two groups of countries. The findings reveal that across the MENA region and the two sub-regions, financial inclusion significantly reduces liquidity risk. However, it increases the level of NPLs in the Gulf Cooperation Council (GCC) countries. Furthermore, findings indicate that banks in the MENA region and the GCC countries benefit from an interaction between financial inclusion and liquidity since it significantly reduces the level of NPLs. Finally, the analysis shows that financial inclusion does not play a moderating role in the relationship between credit and liquidity risks in the NGCC countries. Full article

Globally, financial inclusion is regarded as being crucial for balancing an economy’s financial system. However, despite the significance of financial inclusion, it still needs to be clarified to identify what factors are responsible for the diverse trend of financial inclusion in the forty-five Sub-Saharan Africa (SSA) countries from 1999 to 2024. The main rationale of the study empirically investigated these determinants of financial inclusion in forty-five Sub-Saharan Africa (SSA) countries from 1999 to 2024, which covers three distinct periods: which is the pre-COVID, 2020–2022 is the COVID period, and the post-COVID period from 2023 onward, but examined as a whole from 1999 to 2024 for easy policy formulation for SSA countries. The study was anchored on two main research objectives: firstly, to examine the factors influencing financial inclusion in Sub-Saharan Africa (SSA) in these three distinct periods, and lastly, to present the policy implications of the result of these factors in enhancing financial inclusion in the post-COVID era in SSA. The study used the Panel Least Squares (PLS) technique in the data analysis. The result revealed that economic growth (GRO), Islamic banking (ISMAIC), money supply (MSS), internet users (USERS), and credit availability (CREDIT) positively and significantly enhance financial inclusion with coefficients of 0.001298, 4.926809, 1.08 × 10⁻⁶, 0.459388, and 0.657431, respectively, with significant p-values of 0.0008, 0.0023, 0.0000, 0.0000, and 0.000, respectively. On the flip side, internet servers (SERVER) have a negative coefficient value of 4.63 × 10⁻⁶ with a p-value of 0.000. Though inflation (INFL) and interest rate (INT.) have negative coefficient values of −0.02853 and −0.08317, they have insignificant p-value impacts of 0.2841 and 0.2501, respectively. The result indicates that many of the variables have a significant impact on financial inclusion. This is shown from the probabilities of the t statistics of each of the independent variables in the estimated model, which are significant at the 5% level. The policy implications of these results include the following: firstly, SSA governments should promote economic growth through investment in productive sectors, infrastructure development, and job creation programs to indirectly improve financial inclusion. Secondly, SSA countries’ policymakers should maintain price stability through sound monetary and fiscal policies to ensure inflation does not hinder access to financial services. Thirdly, SSA countries’ governments and central banks should promote lower interest rates and enhance credit accessibility, especially for marginalized groups, through subsidized loans and targeted credit schemes. Fourthly, policymakers should support the expansion of Islamic finance by improving regulatory frameworks and increasing awareness about Sharia-compliant financial products. Full article