Increase In Credit Risk Research Articles

PENGARUH VARIABEL PENERIMAAN DANA ZISWAF, BOPO, DAN LABA/RUGI NONOPERASIONAL TERHADAP NPF GROSS DENGAN FIRM SIZE SEBAGAI VARIABEL MODERASI PERIODE 2018.Q1–2023.Q3

Abstract :This study aims to determine and examine the effect of receiving ZISWAF, BOPO, and non-operating profit / loss on gross NPF with firm size as a moderation variable for the period 2018.Q1 – 2023.Q3. The sample used in this study is companies in the financial sector listed on the Indonesia Stock Exchange (IDX) in 2018-2023. The sampling technique used was purposive sampling, with a total sample of 5 banks for 6 years. The data analysis techniques used are Panel Data Regression Analysis and Moderated Regression Analysis (MRA) with the Eviews 12 application. The results showed that ziswa funds, BOPO and non-operating profit / loss showed a significant influence on the value of the company. This means that if the value of ziswa funds generated is higher, the funds can be used to strengthen the capital of Islamic financial institutions so that the risk of bad loans will be reduced. High BOPO levels have an impact on Gross NPF levels. Large operational costs can reduce the company's profitability. Good non-operating profit can help reduce NPF Gross by improving the company's financial stability and repayment ability, while large non-operating losses can increase credit risk and contribute to an increase in NPF Gross if not managed properly. Firm size shows a significant positive influence on company value. This means that if the resulting capital structure is high, it will cause a decrease in the value of the company, and vice versa. Then, in the interaction of moderation variables, probability can moderate ziswa funds, BOPO, non-operating profit / loss on NPF against the value of financial sector companies in the 2018Q1-2023Q3 period. Keywords: Islamic Banking,ZISWAF Fund, BOPO,profit and loss, NPF Gross, Firm Size.

Liquidity and credit risks during the COVID-19 pandemic: evidence from a dual banking system

Purpose The purpose of this paper is to investigate the relationship between liquidity risk and credit risk of Islamic and conventional banks in a predominantly Muslim country (Indonesia) adopting a dual banking system. Design/methodology/approach To investigate liquidity-credit risk nexus, this study used a sample of 72 Islamic and conventional banks in Indonesia for a period between 2019 Q4 and 2022 Q1. This paper used a generalized method of moments (GMM) and generalized least square (GLS) estimators. Findings This study found that there is a nonlinear (inverted U-shaped) relationship between liquidity risk and credit risk in dual banking system. Liquidity risk was found to increase credit risk if it is below the optimal threshold, and above this optimal threshold, liquidity risk begins to decrease credit risk, both before and during the pandemic. In addition, the impact of liquidity risk on credit risk is higher in Islamic banks compared to conventional banks. Originality/value This paper reinvestigates the puzzle between credit risk and liquidity risk by taking a sample of a dual banking system country and by considering the period of the COVID-19 pandemic. To the authors’ knowledge, this approach has not been addressed in prior empirical studies.

Does financial expertise influence Islamic bank risk-taking?

PurposeThis study investigated how the financial expertise of the board of directors, risk management committee (RMC), audit committee (AC) and Shariá Supervisory Board (SSB) influences the risk-taking of Islamic banks.Design/methodology/approachThe study utilized unbalanced panel data for a sample of 43 full-fledged Islamic banks from 15 countries over 12 years (2010–2021). We employed feasible generalized least squares (FGLS) and heteroskedastic panels corrected standard errors (HPCSE) regression regressions as the primary estimation methods and used a two-step system generalized method of moments (GMM) estimator for robustness checks.FindingsThe results indicate that board financial expertise decreases insolvency and credit risks. Similarly, AC financial expertise and SSB financial expertise reduce insolvency and portfolio risks but increase credit risk. In contrast, RMC financial expertise raises insolvency risk. The remaining relationships are statistically insignificant.Research limitations/implicationsDue to the lack of disclosure regarding the educational and professional background of the board and committee members in the annual reports of some Islamic banks, this research used a sample of only 43 full-fledged Islamic banks operating in fifteen countries from 2010 to 2021.Practical implicationsThe findings can assist both local and international regulators in revising corporate governance codes and risk management guidelines in such a way as to ensure that the financial experts appointed to the board, AC, RMC and SSB, are capable of controlling excessive risk-taking behavior in Islamic banks.Originality/valueThis study contributes to the literature by providing comprehensive empirical evidence that corporate governance financial expertise influences the risk-taking behavior of Islamic banks.

Loan delinquency in private sector banks in Kerala

The Indian Banking Sector faces significant difficulties in recovering debt. The banker must understand the underlying causes of loan delinquency to address the problem efficiently. A delinquent loan becomes a NPL (Non Performing Loan) when the borrower failed to repay the loan for a period of 90 days or more. Delinquency is the sign of increased credit risk, warnings of willful default, poor asset quality management and operational inefficiency. It may help to predict the loan loss provision for the sub standard, doubtful and loss assets. This article explores the various causes of loan delinquencies of private-sector banks operating in Kerala. The analysis revealed that the retails and SMEs registered high level of loan delinquency. A significant difference was found between the old and new generation private sector banks for the Poor loan portfolio management, inadequate collateral, inadequate monitoring and follow-up. From the mean score it is evident that the NPA management in new generation private sector banks is appreciable when compared to old generation private sector banks.

Competition, Credit Risk and Banks’ Franchise Value: Evidence from Kuwait and COVID-19 Policy Insights

Purpose: This paper investigates the franchise-value paradigm theory proposed by Keeley (1990) in relation to the competition-credit risk nexus in Kuwait’s banking sector before and during the COVID-19 pandemic. The study explores the theories of fragility hypothesis, stability, and the non-linear argument, which are subjects of controversy to assess the competitive behavior regarding credit risk. Study design/methodology/approach: Panel data techniques were utilized (OLS, Random and Fixed effects). We divided the sample into two periods: 2010-2019 and 2020-2021 to capture the impact of the external shock. Sample and data: The sample includes five commercial banks operating in Kuwait, with data sourced from annual reports spanning 2010 to 2021. Results: The findings support the “neutral view”, indicating that intensified competition among banks erodes banks’ franchise value and induces credit risk, as posited by the “fragility hypothesis”. Furthermore, higher concentration increases credit risk and insolvency, aligning with the too-big-to-fail and competition-stability notions (Boyd & De Nicolo, 2005; Mishkin, 2006). Notably, during the COVID-19 period, banks’ capital buffers succeeded in absorbing credit risk, nonetheless failed to diversify away from interest-income activities. Originality/value: The study contributes by examining competitive behavior and pricing strategies above marginal costs. It also explores the impact by considering a combination of bank-control variables such as banks’ capital, size, profitability, solvency, and diversification, in relation to competition dynamics and the presence of COVID-19. Research limitations/implications: These findings offer perceptions for policymakers towards dealing with the competition-stability nexus and provide a policy implication on how regulators ought to behave during financial turmoil.

THE INTERPLAY BETWEEN CREDIT RISK AND FINANCIAL PERFORMANCE OF LICENSED SPECIALIZED BANKS: EVIDENCE FROM A DEVELOPING COUNTRY

This paper investigates the influence of credit risk on the financial performance of licensed specialized banks in Sri Lanka from 2006 to 2020, a period marked by economic volatility that added layers of complexity and risk, especially for banks engaged in development lending. Using secondary data from annual reports, the study employs regression analysis to examine this relationship, with the non-performing loan (NPL) ratio as the dependent variable representing credit risk and return on equity (ROE) and return on assets (ROA) as independent variables indicating financial performance. The findings reveal that credit risk significantly impacts the financial performance of these banks, demonstrating a notable negative relationship between ROE and the NPL ratio, as credit risk increases, profitability decreases. These insights are crucial for policymakers to set realistic performance targets and for bank management to allocate capital efficiently and develop strategies to mitigate risk, thereby enhancing financial stability and performance amidst economic uncertainties.

The effect of industry sector and profit-loss sharing financing on credit risk of Islamic banks in Indonesia considering COVID-19 pandemic

Purpose The COVID-19 pandemic has affected economic activity both globally and nationally, which also has an impact to banking sector and Islamic banking is no exception. This study aims to see how the impact of Islamic bank financing in seven sectors affected by the COVID-19 to the credit risk of Indonesian Islamic banks. In addition, this study also tries to see whether the proportion of mudharabah-musharaka or profit-loss sharing (PLS) financing also affects credit risk in Indonesian Islamic banks. Design/methodology/approach This study uses fixed effect panel data regression over the period 2011–2020. Findings The results of this study show that wholesale and retail trade financing will increase credit risk in Indonesian Islamic banks as a policy implication. In terms of the proportion of PLS financing, it shows that a larger share of PLS financing will reduce credit risk in Islamic banks. Originality/value This paper demonstrates that despite the industry’s perception of PLS as riskier than murabaha-based instruments. According to the research, PLS financing will lower credit risk in Islamic banks. This study found that PLS contributes to overall economic stability by shifting the function of Islamic banks from a simple lending body to an active market catalyst/manager/consultant to market players seeking financial aid.

Effects of Negative Interest Rates on Stability and Profitability of Commercial Banks

The article examines the impact of the European Central Bank's (ECB) negative interest rate policy (NIRP) on commercial banks in Europe. It traces the historical context of the policy back to the financial market and banking crises, which eroded trust among banks, leading to liquidity issues and economic downturns. To counteract this, the ECB introduced negative interest rates in 2014, aiming to stimulate the economy.The research question focuses on how NIRP affects banks' annual reports, particularly concerning total assets, credit and risk volumes, proprietary trading, profits, and stability. The hypothesis suggests that NIRP significantly increases risks in bank profitability and stability. Analysis spanning from 2014 to 2022 compares negative interest rate changes with bank balance sheet and profit/loss account developments.Economic theory predicts that negative interest rates decrease bank profits but increase lending activity. Statistical analysis confirms a correlation between NIRP and increased credit risk volume, as well as a shift from bonds to shares in proprietary trading. However, there is no statistical evidence linking NIRP with profit and profitability declines.In conclusion, while NIRP does lead to a significant increase in credit risk volume, it does not halt falling profits and profitability. Therefore, the hypothesis that NIRP increases risks for commercial banks' profitability and stability holds true, posing a threat to financial stability.

Liquidity and Credit Risk in Indonesia: The Role of FinTech Development

This study examines the relationship between liquidity, FinTech development, and credit risk in the Indonesian banking industry. Specifically, it investigates the impact of FinTech, particularly in peer-to-peer lending and payment systems, on credit risk in conjunction with liquidity. The analysis is conducted using panel data from 142 commercial banks in Indonesia over a 15-year period from 2004 to 2018. The results reveal that higher liquidity leads to a reduction in credit risk, whereas FinTech development is found to increase credit risk, particularly in small banks (BUKU 3 and BUKU 4) and private national banks. Notably, this study identifies that the impact of liquidity on credit risk is conditional on the level of FinTech development. Furthermore, the findings suggest that the effects of FinTech on credit risk are contingent on the bank’s characteristics and the economic environment. These results have significant policy implications for designing an inclusive financial framework in the digital era, especially in managing the risks associated with FinTech development. JEL Classification: G231, F31. R10.

Innovations in the repayment structure of microcredit contracts

Abstract Microfinance contracts typically require a fixed repayment schedule that, while ensuring repayment discipline, may inhibit entrepreneurship and business growth. In this article, I review the recent developments in the literature studying innovations in the repayment structure of microcredit contracts. Introducing flexible repayment schedules improves business outcomes by allowing microcredit borrowers to increase investment and to respond to income fluctuations to a higher extent. Although financial innovations hold the promise to foster business growth, and evidence suggests that their demand appears concentrated among financially sophisticated borrowers, they are feared to increase credit risk and hence their adoption among microfinance institutions is very limited. I explore potential challenges lenders face in offering these innovations and outline pathways towards a profitable implementation of such contracts.

Climate change and the European banking sector: the effect of green technology adaptation and human capital

PurposeClimate change poses effect on banking sector’s risks and profitability through adaptation of green technology. This study aims to incorporates green technology adaptation in three sectors: green banking, green entrepreneurial innovation (EI) and green human resource (HR), in a model of bank’s performance. And determines the impact of climate change on bank risk and profitability.Design/methodology/approachAn assessment of profitability and risk profile of commercial banks is done for 27 European countries for 2013–2022, employing a two-step difference system-generalized method of moments estimation technique with a moderate effect of climate change by including interaction between climate change and green technology adaptation.FindingsThe results indicate that green banking increases profitability, reduces credit risk and increases liquidity risk. The results also show that green human resource increases profitability and becomes a source of credit and liquidity risks for the banks. Green EI increases credit risk and liquidity risk, while the effects of green EI on profitability vary with the use of two proxies: Green patents increase profitability and environment, social and corporate governance (ESG) scores decrease profitability.Practical implicationsSupportive government initiatives, including subsidies and tax rebates to green borrowers, may take the burden of green transition off the banking sector.Originality/valueThis paper observes the impact of green technology adaptation in three sectors: banks, EI and HR, moderated by climate change, adding substantially to the existing literature in conceptual framework and methodology.

Pengaruh Kebijakan Moneter dan Makroprudensial terhadap Risiko Kredit di Bank Umum Syariah Periode 2018-2022

Abstract 
 The impact of the financial crisis at the end of 2008 resulted in the financial sector losing its ability to mitigate risk, in turn causing increased credit risk. The aim of the study is, of course, to understand the impact of monetary policy and macroprudential on credit risks in Indonesia's non-allocation financing (NPF). The study USES the data panel that has been processed through eviews 10 and applied with multiple linear regression analysis, specifying five different types of cellular general Banks that fit the criteria as a sample of observation during the 2018-2022 period. Research shows that bi rate as a monetary policy proxy and mandatory minimum requirement (GWM) as a macroprudensian policy proxy does not significantly affect credit risk. However, those capital inequality ratios have a significant negative impact on credit risk, while those variables financing to depositite ratios have significant positive effects on credit risk. Monetary policy and macroprudencies are crucial to systemic risk, particularly credit risk in the financial sector, especially at sharia general bank.

Capital inflow liberalization and bank credit risk

Using a panel of annual data, covering 2207 banks operating in 45 emerging, and developing economies, over the period of 2009–2020, we study the impact of liberalization on capital inflows. Our results indicate that capital inflow liberalization has a robust and positive impact on bank credit risk, as measured by non-performing loans. Upon further examination, we find that the positive effect is more pronounced when bond, money, and financial credit markets, which broaden firms’ financing channels, are liberalized. The liberalization intensifies competition and risk appetite among banks, leading to increased credit risk. The findings suggest that openness reduces banks’ credit growth while improving non-interest income. As expected, this positive effect is mitigated within large and competitive banks, and banks with more assets. Furthermore, we find that tightening macroprudential policies, especially countercyclical capital buffers, can help moderate the positive impact of capital inflow liberalization on bank credit risk.

Venturing into Risk Management: Examining Credit Risk and Performance in Pakistani Commercial Banks through Panel VAR Analysis from a Business Perspective

In Pakistan's dynamic financial sector, effective credit risk management by commercial banks is critical to maintaining financial stability. In this study, we embarked on a unique and comprehensive journey, adopting the Panel Vector Autoregressive (PVAR) analysis, a novel methodology in this context. This approach allowed us to delve into the intricate relationship between credit risk management strategies and the aggregate business performance of commercial banks. The data used in this study spans from 2010Q1 to 2022Q4, investigating the comprehensive nexus of credit risk and macroeconomic indicators using a large dataset encompassing 18 strategically critical commercial banks of Pakistan. Our study uncovers several profound insights, documenting a remarkable increase in credit risk upon increases in the interest rate. The repercussions of the non-performing loans are observed nearly two years after the successive phases of a stern posture of monetary policy have been implemented. Our research findings carry significant weight for the banking industry. We discovered that the levels of credit risk could be reined in due to the protective shield offered by phases of sudden economic booms. This underscores the reinforcing effect of the improving economic conditions on defaults of loans, providing practical and actionable insights for credit risk management strategies.

Impact of Covid-19 on Private Bank Based on SVB

The COVID-19 pandemic has had a profound impact on private banks such as Silicon Valley Bank (SVB). This summary explores the impact of the pandemic on private banking operations, financial performance, and strategic initiatives. The rapid shift to digital banking, driven by lockdowns and social distancing measures, highlights the importance of strong technical infrastructure and cybersecurity measures. Private banks have had to deal with increasing credit risk and market volatility and have therefore had to adapt their lending practices and risk management frameworks. However, private banks focused on sectors such as technology and healthcare have experienced growth opportunities. Effective communication and personalized support are critical to keeping customers engaged during a crisis. It not only describes the causes of the collapse of Silicon Valley banks but also describes what changes government departments, banks, and individuals should make after these social changes, how to avoid these risks, and how to lead the company to a better path of development.

The impact of IFRS 9, liquidity risk, credit risk, and capital on banks’ performance

This study investigates the impact of International Financial Reporting Standard (IFRS) 9, liquidity risk, credit risk, and capital on Jordanian banks’ performance. Aiming to mitigate liquidity and credit risks while ensuring adequate capital ratios to prevent bankruptcy. The study aligns with the findings of Abbas et al. (2019) and Abdelaziz et al. (2022), highlighting the influence of these factors on profitability in the Middle East and North Africa (MENA) region. Data from annual reports of 13 banks listed on the Amman Stock Exchange from 2012 to 2021 was analysed quantitatively, focusing on profitability metrics like return on assets (ROA) and equity (ROE). The results indicate a significant impact of IFRS 9 implementation and a negligible effect of liquidity risk. Notably, an increase in credit risk detrimentally impacts both ROA and ROE. The study also discovers a positive link between bank capital and ROA but a negative association with ROE, underscoring the nuanced interplay between risk management and financial performance in banking.

Factors Affecting Credit Risk in Nepalese Commercial Banks

This study analyzes the factors affecting credit risk in Nepalese commercial banks. The study comprises data from 27 commercial banks from 2002 to 2020 A.D. For analysis, the Least Square Dummy Variable (LSDV) Regression for model I and Random Effect (RE) Regression Analysis for model II were performed. The effect of the independent variables on credit risk, using loan loss provision and non-performing loans, as proxies of it was examined. While comparing both models, the loan loss provisioning was found to better explain the credit risk. The growth rate of GDP, a macroeconomic variable, had a significant and positive effect on credit risk, which was unexpected whereas the control variable, the interbank interest rate, had a negative and significant effect on credit risk. Furthermore, the year dummy showed a relatively high requirement for loan loss provision, especially in the years 2019 and 2020, which may be due to COVID-19. The bank-specific variables like size, and government banks had significant and positive effects on credit risk. This implied that the merging of banks was not fruitful as it caused an increase in the total assets of banks, which would lead to an increase in the size of commercial banks. That increase in the size of commercial banks was found to increase credit risk. In addition, government-owned banks were found to have higher credit risk than other banks. The government should think about reforms through private sector participation in government-owned banks as another alternative to reduce credit risk.

Are green loans less risky? Micro-evidence from a European Emerging Economy

The role played by the banking sector in supporting the green transition has been limited but is expected to increase substantially. We investigate whether the green loans granted by Romanian financial institutions during the period from 2010 to 2020 bear less credit risk compared with other loans in their portfolio. In this respect, we use a novel micro database with information on all green loans granted by a representative share of Romanian financial institutions, combined with debtors’ financial statements. We use different approaches to control for the small share of green loans and find that firms with a sounder financial profile are more likely to access green loans. Using a matched sample of non-green loans, we are able to disentangle the factors that contribute to the increase in credit risk, but we do not observe a significant risk reduction in the case of green loans.

Comprehensive review of different artificial intelligence-based methods for credit risk assessment in data science

Credit risk is the critical problem faced by banking and financial sectors when the borrower fails to complete their commitments to pay back. The factors that could increase credit risk are non-performing assets and frauds which are improved by continuous monitoring of payments and other assessment patterns. In past years, few statistical and manual auditing methods were investigated which were not much suitable for tremendous amount of data. Thus, the growth of Artificial Intelligence (AI) with efficient access to big data is focused. However, the effective Deep Learning (DL) and Machine Learning (ML) techniques are introduced to improve the performance and issues in banking and finance sectors by concentrating the business process and customer interaction. In this review, it mainly focusses on the different learning methods-based research articles available in recent years. This review also considers 93 recent research articles that were available in the last 5 years related to the topic of credit risk with different learning methods to tackle traditional challenges. Thus, these advances can make the banking process as smart and fast while preserving themselves from credit defaulters.

The Role of Artificial Intelligence, Financial and Non-Financial Data in Credit Risk Prediction: Literature Review


 
 
 
 Small and medium-sized enterprises (SMEs) are of major importance in world economies and job creation. Financing is one of the key issues for SME development since SMEs are often considered riskier than large companies. It is argued in the literature that artificial intelligence (AI) and non-financial data could increase the financial inclusion of disadvantaged groups, such as SMEs. This article presents an overview of selected studies on credit risk prediction from the 1960s to 2022, covering topics of research work applying classical statistical methods, studies using AI methods on traditional financial data and studies applying AI methods on non-financial data. Literature overview results showed that the inclusion of non-financial data in credit risk prediction models could increase credit risk prediction performance, while AI methods can enable the inclusion of non-financial data. Since non-financial data potentially could be used as alternative data in credit prediction models, AI and non-financial data could help to increase access to finance for SMEs