Bank Non-performing Loans Research Articles

Impact of financial inclusion, financial stability, bank nonperforming loans, inflation, macroeconomic management quality and unemployment on economic growth in Nigeria

PurposeThe study investigates the impact of financial inclusion, financial stability, bank nonperforming loans, inflation, macroeconomic management quality and the unemployment rate on economic growth in Nigeria.Design/methodology/approachThe data are analyzed using the ordinary least squares regression, generalized linear model regression, robust least squares regression and the quantile regression methods. The sample period is from 2007 to 2022.FindingsFinancial inclusion, inflation rate and macroeconomic management quality are significant determinants of economic growth in Nigeria. Bank nonperforming loans, unemployment rate, international trade and climate change have an insignificant effect on economic growth in Nigeria. Also, financial inclusion, inflation rate, financial stability, macroeconomic management quality and the unemployment rate are significant determinants of economic growth in good economic years in Nigeria.Practical implicationsThe well-known catalysts of economic growth, such as financial inclusion and financial stability, are not positive catalysts of economic growth in Nigeria during good economic years. Therefore, it is recommended that policymakers should find the right level of financial inclusion, financial stability and unemployment that stimulate economic growth in Nigeria.Originality/valueThis study examines some determinants of economic growth in Nigeria which have not been examined in the existing literature.

Board Cultural Diversity and Nonperforming Loans: What Role Does Boardroom Gender Diversity Play?

ABSTRACTIn this paper, we examine the effect of board cultural diversity (BCD) on European banks nonperforming loans (NPLs) and whether boardroom gender diversity (BGD) moderates the BCD‐NPLs relationship. We used a sample of 75 banks in 20 European countries from 2011 to 2022. The System Generalized Method of Moment was performed as an econometric approach. We find that greater BCD increases NPLs and BGD moderates the BCD‐NPLs relationship. The sensitivity analysis results indicate that only large banks benefit from an interaction between BGD and BCD because it lowers the NPLs ratio. Our results are robust to alternative econometric methods.

Corruption, Economic Growth, and Non-performing Loans in Sub-Saharan Africa: An Empirical Analysis (2011–2019)

AbstractThis study explores the impact of corruption and economic growth on non-performing loans (NPLs) in Sub-Saharan Africa (SSA) after the global financial crisis. We use the Arellano-Bond Generalized Method of Moments dynamic panel estimation procedure on 493 banks from 31 Sub-Saharan African countries from 2011 to 2019. We find that corruption and economic growth have significantly positively and negatively influenced NPLs in SSA, respectively. We further investigate how corruption affects NPLs and observe that bank size and NPLs have a positive relationship. Simultaneously, well-capitalized banks and the effectiveness of the judicial system reduce the level of NPLs. The study's uniqueness lies in evaluating the impact of corruption on NPLs at the sub-regional level. The results reveal how corruption has not significantly affected Central and Southern African banks' NPLs but vice versa in West and Eastern Africa. The study concludes that NPLs are a dead weight loss to society. The results confirm how anti-corruption campaigns, improvements in judicial regulation, and sustained economic growth can help mitigate non-performing loans. Furthermore, policy implications such as enhancing institutional quality and implementing growth-sustaining measures have been suggested.

Elections and bank non-performing loans: Evidence from developed countries

Elections and bank non-performing loans: Evidence from developed countries

Corruption’s impact on non-performing loans of banks in emerging markets: Empirical insights

PurposeThis study investigates the impact of control of corruption (COC) on nonperforming loans (NPLs) in South Asian countries. MethodologyThe present study selected three South Asian countries (Pakistan, India, and Bangladesh) from 2000 to 2019. Further, the current research employed the fixed effect model (FEM) analysis on a sample of 81 conventional banks based in South Asian countries. FindingsThe result reveals that control of corruption has a significant and negative association with NPLs, indicating that weak control of corruption would lead to an increase in NPLs in the sample countries. ImplicationsThe findings provide insights to the policymakers in making strategic decisions about NPLs regarding control of corruption impact. OriginalityThe significant increase in NPLs is worrying as it may undermine banks’ ability to grant credit and support a country’s economic recovery. The increasing trend of NPL rates and limited studies in related literature assessing NPLs in the South Asian region has motivated this study, which examines the external and internal factors that may influence NPLs.

Financial security of Ukraine under martial law: Impact of macroeconomic determinants

Russia’s open aggression against Ukraine has resulted in significant changes across all sectors of the Ukrainian economy and its financial sphere, including financial security. The paper aims to identify the impact of the primary macroeconomic determinants, i.e., military defense spending, non-performing bank loans, exchange rate, foreign debt, and state (total) reserves, on the financial security of Ukraine under martial law. The canonical correlation analysis is employed to assess the strength of the relationship between the above macroeconomic indicators and the level of the state’s financial security. It was found that the reduction of the state’s financial security level in 2022 was 63.9%, explained exactly by the changes in the above macroeconomic determinants after the start of a full-scale invasion. The study determined the degree of influence of each indicator on Ukraine’s financial security level. An increase in the level of military defense spending, non-performing bank loans, hryvnia’s devaluation, and external debt growth had a direct negative impact on Ukraine’s financial security. At the same time, an upsurge in total reserves had an indirect negative impact (through the external debt growth). The research findings confirm the necessity for effective monitoring and management of the macroeconomic indicators to maintain both Ukraine’s financial security and macro-financial stability in order to ensure its’ sustainable economic development during the postwar recovery period. AcknowledgmentThis research is financially supported by the NATO SPS Program “Security of territorial communities: evidence from the Eastern European countries”.

How do Macroeconomic Indicators Shape Nonperforming Loans?

This study examines the influence of macroeconomic indicators on nonperforming bank loans. This research focuses on the period from 2010:1Q to 2019:4Q to capture significant trends and fluctuations in the economy. Data for receivables to be liquidated as a proxy for nonperforming loans, the consumer price index as a proxy for inflation, total private consumption expenditures as a proxy for economic activity, gross domestic product and total (private) fixed capital expenditures as proxies for economic growth are analyzed using the ARDL bound test, FMOLS, DOLS and VECM Granger methodologies. This study addresses several key questions. First, it examines how the receivables to be liquidated relate to changes in total private consumption expenditures (LNPCE). The findings indicate that higher LNPCE decreases the ability of receivables to be liquidated in both the long run and short run. Second, it explores the impact of gross domestic product (GDP) fluctuations on the amount of receivables to be liquidated, revealing that a higher GDP increases the amount of receivables to be liquidated in both the long and short run. Last, the study assesses the extent to which changes in the consumer price index (CPI) influence the receivables to be liquidated, finding that a higher CPI increases the receivables to be liquidated in the long run.

Pengaruh CAR, BOPO, ROA dan BI RATE terhadap NPL Bank

This research aims to evaluate the impact of Capital Adequacy Ratio (CAR), Operational Expenses on Operating Income (BOPO), Return on Assets (ROA), and BI Rate on Non-Performing Loans (NPL) of Banks in Indonesia from 2019 to 2021. Method used is panel regression analysis with data from the financial reports of 43 banks published by the Financial Services Authority (OJK). The sample includes banks that are listed on the Indonesian Stock Exchange and have complete data for that period. The research results show that CAR does not have a significant influence on bank NPL, indicating that the availability of bank capital does not significantly influence the level of bank non-performing loans. On the other hand, BOPO has an effect on bank NPLs, where high operational costs and low operating income tend to increase the bank's level of non-performing loans. ROA also does not have a significant effect on bank NPL, indicating that the rate of return on bank assets does not substantially influence the level of bank non-performing loans. However, the BI Rate has a significant influence on bank NPLs, indicating that Bank Indonesia's benchmark interest rate (BI Rate) has a significant impact on the level of bank non-performing loans. In conclusion, the research emphasizes the importance of managing operational efficiency and paying attention to changes in the BI Rate to control credit risk and maintain a healthy NPL level. Keywords: CAR, BOPO, BI RATE, NPL, ROA

Analysis of Machine Learning in Classifying Bank Profitability with Corruption Factor

Corruption, which is generally defined as the abuse of authority for personal benefit, is not a recent phenomenon and has become a major issue in almost all countries throughout the world. Indeed, a high level of corruption increases bank non-performing loans which in turn reduces profitability and intensifies the fragility of the banking industry. Given the adverse impacts, corruption has been used as one of the factors in bank performance evaluation. As research on corruption-bank performance with machine learning techniques is rarely reported in the literature, this paper presents the empirical comparison of different machine learning algorithms for classifying bank profitability. Besides machine learning performance comparisons, this paper presents the analysis of machine learning features importance to justify the effect of corruption factor in the different machine learning algorithms for classifying bank profitability. The results indicated that all the tested machine learning algorithms present a good ability of classifying bank profitability at accuracy percentages above 70% but corruption index has contributed very minimal effect to the machine learning performances. The framework of this research is highly reproducible to be extended with a more in-depth analysis, particularly on the bank profitability factors as well as on the machine learning algorithms.

Bank non-performing loans, loan charge-offs, and crime incidence

Bank non-performing loans, loan charge-offs, and crime incidence

Impact of Institutional Environment on Banks’ Non-Performing Loans: Evidence from BRICS Countries

The drivers of non-performing loans (NPL) and the possible effects of the institutional and business environments on the credit risk exposure of banks in the panel of BRICS countries and segregated models are analyzed in this paper. The purpose of the study is to identify the relationship between banking, macroeconomic and institutional factors of non-performing loans of banks at the BRICS level for the period 1996–2020. The panel ARDL approach is used for this purpose. The Panel Granger causality test is applied to verify the hypothesis of the relationship between economic development and NPLs. Panel co-integration tests examine the existence of a long-term link between the same two variables. The results of the study demonstrated that a decrease in the proportion of NPLs results from boosting performance metrics like the Z-score. Because the banking industry has more resources as a result of higher financial development and/or financial intermediation, the amount of NPLs is reduced. Finally, our study demonstrates how important the institutional environment is for raising the quality of bank credit. It was concluded that the low level of NPLs in BRICS countries was largely linked to more effective anti-corruption management, robust regulatory standards, increased application of the rule of law, freedom of speech and accountability.

Dampak Non Performing Loan Terhadap Peningkatan Pendapatan Perusahaan di Sektor Jasa Perbankan

It is hoped that the results of this research can be used as input and consideration for companies in making decisions and establishing policies to overcome problems related to the level of Non-Performing Loans of banks, especially Rural Banks. The population of this research are customers who use credit services who have experienced problems, especially in the non-performing loan category. The research uses quantitative research methods with analysis using the SPSS application and using multiple regression analysis techniques. In this research, the results can prove that the results of Non-Performing Loans will influence the increase in income. The results of the t-test analysis = 3.578 means that the hypothesis can be accepted, because the t-test > tcount. namely 3.578 > 3.078, meaning there is a correlation between the Non-Performing Loan variable and an increase in company income. Keywords: non-performing loans, increasing income, banking

Financial fragility, human resource management, and transition to renewable energy in Asian economies: a comparative analysis.

The main hurdle in deploying renewable energy projects is the high initial cost, making it difficult for businesses and individuals to afford it. The fragility of the financial sector and human resource management further slows the pace of renewable energy demand. Therefore, we aim to investigate the impact of financial fragility and human resource management on renewable energy consumption over time horizon 1997-2020. To that end, the analysis employed the ARDL-PMG model. For Asia as a whole and all other sub-regions, including South East Asia, East Asia, South Asia, and Western Asia, the estimates for bank non-performing loans are notably negative. In general, these findings imply that a rise in financial fragility significantly reduces renewable energy consumption in the long run. In the short run, the estimates attached to both bank non-performing loans and bank costs are negatively significant in Asia and sub-regions of Western Asia only. The results for the human resources show that it exerts a significant and positive influence on renewable energy demand in Asia as a whole, South Asia, East Asia, and Western Asia. The estimates attached to human resources are statistically insignificant in all models in the short run. In the end, some important public strategies and their implementations have been discussed.

Macroeconomic Variables and Non-Performing Loans of Banks in Nigeria

The banking sector holds immense importance in any economy. However, the non-performing loans of Nigerian banks are a concern for the economy and financial stability. This can be attributed to the effects of macro-economic factors on banking activities in the country. The study aimed to examine macroeconomic variables and the non-performing loans of banks in Nigeria. A descriptive research design method was used for the study. Secondary data were collected for the period from 1990 to 2021. The auto regressive distributed lag (ARDL) error correction model was used for data analysis. The study’s results show that tax revenue, recurrent expenditures and the real interest rate will in the long run resolve the problems of non-performing loans of banks in Nigeria. Contrarily, money supply and exchange rate, if not properly managed, may amplify non-performing loans of banks in Nigeria. The study concluded that macroeconomic variables, when properly devised, will help subdue the problem of increasing non-performing loans in Nigeria.

Green growth strategies in Asia: unleashing the heterogeneous asymmetry of ICT capital, financial fragility, environmental policy stringency, and education.

Financial fragility, ICT capital, environmental policy stringency, and education are the main factors that have also gained popularity regarding their impact on green growth. This study examines the impact of financial fragility, ICT capital, environmental policy stringency, and education on green growth. For analyzing the short- and long-run estimates, we have applied the panel QARDL model. The results of the panel QARDL model highlight that the estimates of non-performing bank loans and bank costs are negatively significant in both the short and long run, implying that financial fragility hurts green growth in the short and long run. Similarly, the estimated coefficients of the internet (mobile) and education estimates are positively significant in the short and long run, confirming that ICT capital and education are causing green growth, while environmental policy stringency promotes green growth only in the long run. Regarding the asymmetric effects of all the factors on green growth, the Wald test only confirms asymmetric effects in the long run. The study offers several significant recommendations for sustainable green development policies.

Determinants of Non-Performing Loans in a Small Island Economy of Fiji: Accounting for COVID-19, Bank-Type, and Globalisation

An increase in non-performing loans and bad debts in the banking sector can make banks vulnerable to a loss of confidence among customers and other banks and a banking collapse. The recent pandemic (COVID-19) and the evolving globalisation can affect bank operations, although the effects may depend on the type of banks and other bank-specific factors. In this paper, we revisit the topic on the determinants of non-performing loans of banks in a small island economy of Fiji over the period 2000 to 2022. We apply a fixed-effect method and consider seven banks (five commercial banks and two non-bank financial institutions). In our estimations, we examine the effect of bank-specific factors and control for the social and economic globalisation, the GFC, the COVID-19 pandemic, and bank-type effects, as well as the effect of the interaction between the bank type and the pandemic, as key contributions of the study. Overall, our results are consistent in terms of the effects noted from the bank-specific factors. From the extended model estimations, we note that COVID-19 had a more adverse effect on loan losses than the GFC, and the interaction between the bank type and COVID-19 indicates that non-banks were highly vulnerable to loan losses, whereas commercial banks exhibited greater preparedness. Economic globalisation reduces bank losses, whereas social globalisation exacerbates NPLs.

Nonperforming loans and related lending: Evidence from Ukraine

This study examines bank-specific factors that determine nonperforming loans (NPLs) in Ukraine. Analysis of an unbalanced sample of 207 banks from 2008 to 2020 reveals that the NPLs of banks increase with related lending, suggesting that related lending is detrimental to the soundness of bank loans owing to the standard information advantage that can be offset by the bank's conflict of interest in banking relationships. Moreover, a positive shock to NPLs causes a substantial increase in related lending. These results highlight the importance of close monitoring of banks' lending practices to related parties for suppressing excessive risk-taking behavior of banks.

Nudge and policies based on behavior as a powerful tool in reducing Nonperforming bank loans

Nudge and policies based on behavior as a powerful tool in reducing Nonperforming bank loans

Fintech inputs, non-performing loans risk reduction and bank performance improvement

The function of Fintech is preventing and resolving financial risks, and the ability of small and medium-sized commercial banks to apply Fintech to resolve non-performing loan risks deserves attention. This paper uses as a sample the micro-survey data of 432 branches of the city commercial banks in Beijing from 2005 to 2022 and constructs an econometric model of the risk reduction effect of Fintech on non-performing loans.The findings are as follows.Firstly, Fintech inputs can significantly reduce the risk of non-performing loans. For every 1% increase in IT personnel inputs, software inputs, and hardware inputs, the non-performing loan ratio will reduce by 0.091%, 0.055%, and 0.024%, respectively. In other words, IT personnel inputs contribute the most to the reduction of non-performing loan risk, followed by software inputs.Fintech has a certain lag effect in alleviating the risk of non-performing loans in banks and tends to strengthen over time.Secondly, Fintech inputs has an indirect effect on banks' performance by reducing non-performing loan risk, And there is a positive feedback loop between Fintech inputs, non-performing loan risk mitigation, and improving performance. This effect is not significant in the current period but significant when lagged by three periods.Thirdly, Fintech inputs has a significant inhibitory effect on non-performing loans loans of concern and subprime. For every 1% increase in inputs in IT personnel, software, and hardware, concern will decrease by 0.263%, 0.358%, and 0.107%, respectively, while subprime will decrease by 0.115%, 0.216%, and 0.057%, respectively. Software and personnel inputs have a greater inhibitory effect on the above two types of loans than hardware inputs. Fourthly,mechanism analysis shows that data governance application, compliance enforcement, and internal control enforcement have a moderating effect on Fintech input's impact on banks' non-performing loan risk.

Corruption‐induced bank nonperforming loans

AbstractBy introducing China's anticorruption movement, we establish the causal effect of corruption on nonperforming loans (NPLs). Through manual collection of all publicly available bank data and difference‐in‐differences (DID) regression analysis, the results show that the anticorruption movement significantly reduces NPLs, indicating that corruption leads to NPLs. In addition, the anticorruption movement is more effective in reducing NPLs for banks with higher risks, suggesting the existence of risk prevention mechanisms. Finally, our main conclusions are more pronounced in state‐owned commercial banks, banks located in regions with strong legal environment, and unlisted banks. Overall, this paper argues that corruption is also a factor leading to NPLs and provides solid empirical evidence for the anticorruption movement to reduce NPLs in China.