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Nonperforming loans play a critical role in financial institutions' overall performance and can be controlled by forecasting the probable nonperforming loans. This paper employs a series of machine learning techniques to forecast bank nonperforming loans on emerging countries' financial institutions. Using quarterly cross-sectional data of 322 banks from 15 emerging countries, this study finds that advanced machine learning-based models outperform simple linear techniques in forecasting bank nonperforming loans. Among all 14 linear and nonlinear models, the random forest model outperforms other models. It achieves a 76.10% accuracy in forecasting nonperforming loans. The result is robust in different performance metrics. The variable importance analysis reveals that bank diversification is the most critical determinant for future nonperforming loans of a bank. Additionally, this study revealed that macroeconomic factors are less prominent in predicting nonperforming loans compared with bank-specific factors. [ABSTRACT FROM AUTHOR]

This study explores the effect of fintech-driven inclusive finance on the profitability of banks using an unbalanced panel dataset from 660 banks across 40 developing countries between 2011 and 2021. We start with a fixed-effect estimate and subsequently validate our main findings using two-stage least squares (2SLS-IV), two-step system generalized method of moments (GMM), and generalized least squares (GLS) methodologies. Our analysis centers on three key profitability metrics: ROA, ROE, and NIM. Our findings suggest that fintech-backed inclusive finance boosts ROA by 9.10%, ROE by 18.87%, and NIM by 7.98%, highlighting the growing importance of mobile, internet, and agent banking in these nations. We also note that large banks benefit more from inclusive finance than small ones. Additionally, conventional banks see a more marked improvement in profitability than Islamic and savings banks. The relationship between inclusive finance and bank profitability is stronger in countries with higher GDP growth and those actively advancing financial inclusion through fintech, compared to countries with slower GDP growth and less emphasis on financial inclusion. When examining the interaction effects, the COVID-19 pandemic has further emphasized the positive connection between fintech and bank profitability. This suggests that fintech-driven inclusive finance can play a role in enhancing bank profitability, even in challenging times like the COVID-19 period. The transition towards fintech, however, mandates substantial investments, enhanced financial literacy, and heightened customer security, presenting persistent challenges for governments, policymakers, regulators, and financial institutions. [ABSTRACT FROM AUTHOR]

This paper primarily examines the quadratic effect of banks' size on capital regulation and risk-taking behavior by using simultaneous equation approach. This paper primarily examines the quadratic effect of banks' size on capital regulation and risk-taking behavior by using simultaneous equation approach. To carry out the objective, this study has been built on the two-stage least squares (2SLS) method for a dynamic unstructured panel data of 85 banks from the Central European banks for the period 2012–2017. There is a positive and significant relation between regulatory capital and risk. Also, higher risk-taking behavior causes banks to sacrifice their stability. This study also finds that there is a negative correlation between bank size and capital, indicating that larger the bank size lower tendency to keep capital more. In similar way, there is also a negative association between bank size and risk taking, indicating that lower tendency of taking risk by large banks and vice-versa. Finally, this paper can be used as a medium of information for the stakeholders of banks and others financial institutions of the country. There is a dearth of literature which was built on the quadratic effect of bank size regarding recent financial regulation and risk. [ABSTRACT FROM AUTHOR]

The main object of this research is to find out the nexus of banks' competition, ownership structure, and economic growth on credit risk and financial stability. In addition, it examines the level of financial stability, economic growth, and ownership structure in the Middle East and North African (MENA) economies. The generalized method of moments (GMM) method was used to examine this study. The study used an unbalanced panel dataset from 2011 to 2021 in MENA countries. This research demonstrates a negative relationship between economic growth, credit risk, and financial stability in MENA economies; nevertheless, it proves an insignificant effect among them. It also shows that the lower the level of bank competition, the lower the level of bank risk taking, and the better the level of financial stability. It further found that market competition and bank ownership structure had a homogenous effect on financial stability when looking at the impact of competition and bank ownership structure. In the long-term sense, the square term of competition is highly favorable with financial stability models ((Lerner square × Islamic banks), (Lerner square × commercial banks), (Lerner square × specialized government institutions)). However, financial stability improves with time, as seen by the competition square term bank ownership structure (a square measure of competition) with the Lerner index (LI) and the Herfindahl–Hirschman index total assets (HHIA). This finding of the square measure of competition is supported by competition stability theory. However, this study also proved that Islamic and commercial banks are less vulnerable to credit risk than specialized government institutions (SGI). This study scrutinized how MENA economies can remain stable through banking competition. This study builds a new brand of literature review. As a result, this research gives MENA policymakers better ideas for making policies that help the banking environment. [ABSTRACT FROM AUTHOR]

Economic growth necessitates the development of human capital and education. It plays a critical and necessary role in the formulation of income distribution policies and alleviating poverty. This study investigates the relationship through ordinary least square (OLS), fully-modified OLS and dynamic OLS models using panel data from the South Asian Association for Regional Cooperation (SAARC) countries from 1990 to 2018. According to the findings, imbalance plays an important role in influencing poverty and concludes that the government should embrace procedures that help improve pay distribution to reduce poverty at the strategy level. Furthermore, the findings state that a bi-directional Granger causality exists between schooling and poverty. In terms of strategy, SAARC countries should continue to increase the proportion of sustainable energy used for financial development, thereby decreasing the use of fossil energy for environmental improvements. Additionally, this study shows that the association of pay disparity hoses the positive effect of financial development on poverty, and it supports the contention that the degree of imbalance reduces the impact of comprehensiveness. Pay disparity is now a critical determinant of poverty. [ABSTRACT FROM AUTHOR]

"The core purpose is to explore the relationship between competition, loan quality, ownership structure, and risk for MENA economies." In addition, this study examines the financial stability level of dual banking and explores the bidirectional causality of competition and risk concerning the impact of ownership structure. This study uses 748 observations from 2011 to 2020 in MENA countries. The Generalized Method of Moments (GMM) is an econometric technique used to estimate the parameters of a statistical model. The study findings indicate a negative (positive) relationship between MENA bank competition and risk (financial stability). It indicates that lower bank competition reduces bank credit risk and increases financial stability in MENA countries. Regarding ownership structure, Islamic banks display a stronger position in MENA economies than that of Commercial banks and Specialized Government Institutions. In contrast, specialized government institutions are riskier than commercial banks and Islamic banks. Loan quality shows the two-way causality between the degree to which banks compete and the quality of their loans to customers in the MENA markets. This study sets itself apart from other studies by creating a new segmented literature review portion. Finally, a significant policy implication is provided for academics, researchers, and policymakers interested in applying these findings. [ABSTRACT FROM AUTHOR]

The main purpose of this study is to identify the impact of intellectual capital efficiency (ICE) also known as knowledge capital along with its components human capital efficiency (HCE) and structural capital efficiency (SCE) on bank risk-taking behavior in Bangladesh. To reveal this effect, the study uses generalized method of moment (GMM) estimator and Two Stages Least Square estimator (to check the Robustness) and unbalanced panel data of 32 commercial banks of Bangladesh consisting of 530 bank-year observations during the year 2003-2020. The main results of the study are: (a) ICE is significantly and positively connected with a bank's credit risk which indicates credit risk grows up with the increase of Intellectual capital efficiency, and (b) Both the human capital efficiency and structural capital efficiency positively impacts credit risk but the impact of SCE is not significant as HCE, (c) Bank performance (ROA), RWATA, macro variable inflation, and size have a negative impact on bank risk whereas ID and GGDP insignificant positively impact on bank's risk. Finally, the results of the study will assist the stakeholders, policymakers, and academicians for future research. [ABSTRACT FROM AUTHOR]

Bangladesh has been encountering a budget deficit since 1972 because of a decrease in the source of income. This paper aims to examine the effect of budget deficit financing on economic growth in Bangladesh throughout 1981–2018. Using secondary data, the paper uses the cointegration test, vector error correction mechanism (VECM) and Granger causality test. Johansen's cointegration test outcomes find that the study variables are cointegrated and subsequently have a long-run nexus among the variables. The study finds that in the long run, government domestic debt (GDD), government external debt (GEXD) and money supply (MS) affect positively economic growth (RGDP). The outcomes of the VECM approach express that in the short run, GDD, external debt and MS negatively affect economic growth. Also, short-run causality runs from the GDD, GEXD and MS to economic growth. The Granger causality test result shows unidirectional causal nexus running from GDD to RGDP, RGDP to external debt and GEXD to MS, and bidirectional causal nexus between MS and GDD in Bangladesh. The study suggests the governments should enhance moderate levels of domestic and external borrowing and uses it in productive and efficient ways to accelerate economic growth in Bangladesh. [ABSTRACT FROM AUTHOR]