Credit Risk Indicators Research Articles

Assessment of the banking sector's exposure to hydrometeorological events in Costa Rica

This study examines, for the first time, the exposure of the credit portfolio of the banking system in Costa Rica to hydrometeorological events, specifically excess rainfall events, with a focus on firm credit at the canton level. We propose a credit risk indicator to identify cantons with credit portfolios that are more affected by rainfall events. Moreover, we introduce a novel approach with respect to firm level data to assign a single productive location to firms with two or more establishments. We find that cantons with the highest number of excess rainfall events represent a small share of the average credit balance of the country. Furthermore, we observe that the top three cantons with the highest credit risk score are driven by economic activities that are not expected to be notably vulnerable to extreme rainfall.

Influence of Capital Adequacy Ratio, Credit Risk, Market Risk and Financial Distress Indicator towards Stock Return

The research objective is to the influence of capital adequacy ratios, credit risk, market risk, and financial distress indicators on stock returns. The sample uses a saturated sampling method. The data used is secondary data collected using the documentation method. Independent variables include indicators of capital adequacy ratio, credit risk, market risk, and financial distress with the dependent variable being stock returns. The analysis uses multiple regression. This research found that: capital adequacy ratio, credit risk, market risk, and financial distress have no effect on stock returns.

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.

Profitability of Commercial Banks in Portugal and Spain: A Panel Data Analysis Model

The Portuguese and Spanish banking system, in the framework of the economic and financial crisis suffered a significant reduction in the profitability of its banking business. Taking into consideration the problem of profitability in the banking sector at a global level, some studies have been increasingly highlighted both in academia and in the financial market. Thus, this paper aims to analyze the determinants of banking profitability of banks operating in two different financial systems, Portugal and Spain, for the periods from 2014 to 2019. To obtain the results, we used a panel data analysis model that combines cross-section (banks) and time-series (years) data, obtaining a strongly balanced panel. Multiple linear regression models were then used and it was possible to identify credit risk, solvency and operational efficiency as the main factors explaining bank profitability. Finally, the results show that the high credit risk and operational efficiency indicators of these banks have a negative significant influence on their profitability. In turn, more robust solvency indicators have a positive significant dominant on bank´s performance.

Credit Risk and its Impact on Earnings of Nepalese Finance Company

This study has examined the impact of credit risk on earning performance of Nepalese finance companies. The descriptive and causal-comparative research designs have been adopted for the study. The pooled data of four finance companies out of seventeen for the period of 2074/75 to 2078/79 have been analyzed using a regression model via SPSS. Impairment charge ratio and non-performing loan ratio are independent variables whereas interest spread rate, profit margin, and return on assets are the dependent variable. The regression results revealed that there is a significant and positive relationship between interest spread rate and credit risk indicators, the non-performing loan ratio has an insignificant and negative effect on earnings performance and the impairment charge ratio has an insignificant but somewhat positive effect on the earnings performance of finance companies of Nepal. Nepalese finance companies should strictly follow the prevailing NRB Directive as well as Basel II Accord while managing credit risk and finance companies should use their effort to reduce non-performing loans.

Inferred Rate of Default as a Credit Risk Indicator in the Bulgarian Bank System.

The inferred rate of default (IRD) was first introduced as an indicator of default risk computable from information publicly reported by the Bulgarian National Bank. We have provided a more detailed justification for the suggested methodology for forecasting the IRD on the bank-group- and bank-system-level based on macroeconomic factors. Furthermore, we supply additional empirical evidence in the time-series analysis. Additionally, we demonstrate that IRD provides a new perspective for comparing credit risk across bank groups. The estimation methods and model assumptions agree with current Bulgarian regulations and the IFRS 9 accounting standard. The suggested models could be used by practitioners in monthly forecasting the point-in-time probability of default in the context of accounting reporting and in monitoring and managing credit risk.

Ethnic politics and sovereign credit risk

How does domestic politics affect sovereign credit risk? To date, scholars have largely focused on how economic interests along class-cleavages influence sovereign default risk and borrowing costs. Ethnic dynamics are another important political factor that explains governments’ creditworthiness, yet are understudied. We investigate how ethnic politics shape governments’ credit access and argue that the fiscal incentives generated by ethnic coalitions influence credit risk differently than those created by class cleavages. Because ethnic coalitions are usually smaller than class coalitions, left governments with ethnic support can commit to lower spending and receive more favorable risk assessments. Right governments that rely on ethnic support, however, will have greater spending demands because of their need to satisfy ethnic groups. We test our argument using a new indicator of government ethnic support and four indicators of sovereign credit risk. We find that, in emerging markets, the borrowing costs of right governments increase as they become more dependent on ethnic groups for political support. Our findings suggest that financial markets are attuned to multiple dimensions of domestic politics and demonstrate that ethnic divisions can have strong implications for governments’ access to credit.

Review of theoretical literature: The relationship between credit risk management and bank profitability

Today, commercial banks are the largest financial institutions in our country. Credit risk is one of the biggest risks of these banks due to the nature of their activities. Through effective credit risk management, banks not only support the sustainability and profitability of their business, but also contribute to systemic stability and an efficient distribution of capital in the economy. This paper will focus on the theoretical analysis of the relationship between some indicators of credit risk management and indicators of bank profitability, as well as the evidence of the stability over time of this relationship.

Potential risks of liquidity and credit affecting the efficiency of Islamic banks in Bangladesh

Recently worldwide Islamic finance has gained considerable attention. However, Islamic financial institutions face multiple risks to sustaining and growing further. Against this backdrop, the paper examines the impact of both liquidity and credit risk on the efficiency of Islamic banks (IBs) operating in Bangladesh. This paper uses IB’s data from 2007 to 2018 and offers a two-stage assessment. In the first stage, it uses data envelopment analysis (DEA), and in the second stage regression models to assess the impact of both liquidity and credit risk on the efficiency of the IBs. Efficiency scores confirm that IBs are operating with an 86% efficiency level through a 68% share in the constant returns to scale (CRS). Our results also confirm that both liquidity risk (LR) and credit risk (CR) have a significant impact on the efficiency of the IBs in Bangladesh. A higher score for efficiency is shown by a higher liquidity risk, whereas mixed results are confirmed by credit risk indicators. Moreover, the Z-score (a bank stability measurement) and number of branches (a measurement of the bank’s network coverage), have a positive impact on efficiency. On the other side, the size of the bank and the financial crisis period show a negative relationship with the bank’s efficiency. The findings of our paper significantly contribute to the Islamic banking sector, especially for the policymakers and academic researchers.

Volatility spillover networks of credit risk: Evidence from ASW and CDS spreads in Turkey and Brazil

This study examines received and transmitted volatility spillovers of Credit Default Swap (CDS) and Asset-Swap Spread (ASW) for Brazil and Turkey. The empirical analysis is implemented using two country-based (stock markets and exchange rates) and two global (volatility index and global economic activity index) variables to account for the impact of integration into global markets. Empirical results suggest that both countries display distinctive features in their spillover networks. While exchange rates and the stock market figure prominently in Brazil as a source of spillovers, for Turkey, the primary element in spillovers appears to be credit risk indicators. Time-varying analysis results show that the European Debt Crisis of 2010-2011 and the global liquidity crunch of 2018-2019 are two critical periods in volatility spillovers that occurred toward credit risk indicators. Brazil displays more sensitivity to the developments of the pandemic than Turkey, likely due to its dependence on global economic activity and energy prices. Finally, for both countries, the leading variable in spillovers to credit risk indicators during financial turbulence episodes appears to be foreign exchange markets. This result highlights both economies' fragility and vulnerability to foreign exchange market-based shocks. Thus, we suggest effective and solid measures in this regard. Otherwise, those shocks could potentially induce a higher cost of financing in both economies due to the negative impacts on CDS and ASW spreads.

Digitalization of corporate business of Ukrainian banks

Introduction. Increasing competition bet­ween banks requires the introduction of banking products with a new service and economic design, based on modern software, technology and information platforms. Problem. Digitalization is becoming a key trend in conducting business for banks and their corporate clients. The aim of the study is to cluster banks by the level of digitalization and determine the relationship between it and indicators of market power, financial performance and cre­dit risk. Methods. Input normalized indicators for 32 banks of Ukraine, determined using the MINIMAX methodology, were used. The study was based on correlation-regression and cluster analysis. Results. The information base for calcu­lating the digitalization index for banks in the focus group was chosen based on the number of: the number of visitors to banks’ websites, regis­tered users of banks’ mobile applications (inclu­ding for legal entities and individuals), branded online inquiries, banking self-service devices, sub­scribers of banks in social media networks. When determining the level of digitalization in corpo­rate business, only two indicators were used: the number of registered legal entities that use mo­bile bank applications and the number of brand-name online searches for each of them. Three hypotheses were put forward and their empirical verification was carried out, accor­ding to the results of which it was established that there is a moderate correlation between the digitalization index and the credit risk indicator and a low correlation between the digitalization index and indicators of financial performance and market power. Among the financial indi­cators a noticeable correlation was found only between the level of the interest margin and the level of digitalization. Conclusions. For most of the banks in the focus group, a low level of digitalization is inhe­rent in the corporate business. It is proposed to develop a strategy for the development of the corporate business of banks on a new techno­logical platform, which will make it possible to extend digitalization processes not only to typi­cal, but also to exclusive financial services pro­vided to corporate clients, taking into account their individual service.

Determinanty výnosnosti evropského bankovního systému v letech 2012-2019

This paper aims to find the microeconomic and macroeconomic determinants of European bank profitability from 2012 to 2019 using the regression model with the multicollinearity condition as a matrix parameter, the multicollinearity below the defined value, ensuring regression model reliability. The bank sector profitability is measured by return of average equity, return of average assets and net interest margin as dependent variables. The research creates a set of independent variables based on a literature review. The model is built on a sample of 3,257 European commercial banks for all EU countries excluding Romania due to missing data, and the input data were obtained based on the Orbis Focus Bank and the World Bank Database. The results revealed that the cost to income ratio and loan loss reserves to gross loans are the most important determinants of profitability of European commercial banks as measured by return of average assets. The results also show that GDP growth rate, inflation measured by the consumer prices and loan loss reserves to gross loans are the most important determinants for the net interest margin indicator. We recommend that commercial banks optimize the cost structure, create sufficient reserves, monitor the process of digital transformation and monitor credit risk indicators.

The Impact of Credit Risk and Bank-Specific Drivers on Banks’ Performance: Evidence from the UAE Region

The COVID-19 pandemic has induced a series of credit risk problems for most commercial banks in the GCC region. Thus, the current paper aims to examine the impact of both credit risk and bank-specific drivers on commercial banks’ financial performance in the UAE from the period 2017 - 2021. The study used NPLs, LLP, and DR as credit risk indicators while CER, LR, and NPLs were used as bank-specific drivers and ROA as financial performance measures. The Random Effect model was used for data analysis. The findings revealed that NPLs and LLP had a negative and significant effect on ROA while CER, LR, and, NPLs were found to have a negative and significant relationship with ROA. This paper implies that banks need remain prudent in their credit risk management and adopt the best strategies to manage and control bank-specific drivers to improve their performance

Data-driven decision-making in credit risk management: The information value of analyst reports

Other than banks, non-financial companies also continuously monitor and analyze their credit risk exposure to avoid possible counterparty defaults. Credit default swaps are commonly used financial instruments that provide information on a counterparty's creditworthiness. Although this metric can provide crucial insights, the underlying price dynamics often remain unknown and require further explanation. Data-driven decision-making is a key concept for identifying these reasons and supporting and justifying decisions. In this paper, we provide such justifications by applying sentiment and topic analysis to company-related financial analyst reports. While the contents of financial news have been analyzed in the past, analyst reports can offer additional insights, as seasoned analysts use them to disseminate in-depth research to experienced investors. This analysis examines 3386 analyst reports covering constituents of the Dow Jones Industrial Average Index in the period from 2009 to 2020. The results suggest that even when established credit risk indicators and financial news are considered, the sentiment and a subset of topics are correlated with changes in the credit default swap spread, indicating a fundamental relationship between quantitative risk metric and analyst reports. We find that analyst reports contain information related to the change in credit default swap spreads, an insight that helps to improve our understanding of existing risk assessments. The outcome indicates that banks or corporate risk managers can benefit from complementing established financial metrics and even financial news data with new insights derived from analyst reports.

АНАЛІЗ КРЕДИТНОЇ ПОЛІТИКИ БАНКІВСЬКОГО СЕКТОРУ УКРАЇНИ

The article is devoted to issues of the banking system of Ukraine. In modern conditions regarding the functioning and development of banking in the country, the creation of the credit policy of Ukraine occupies an important place. If the bank's credit policy is effective, then the banking risk is reduced and the bank's profit increases, even in crisis conditions of economic development. To assess credit policy, such categories as: credit portfolio, amount of non-performing loans and compliance with NBU regulations were analyzed. The dynamics of the entire amount of loans issued was studied, as well as the structure of the credit portfolio of the banking sector of Ukraine by type of borrower during 2018-2022 was analyzed. The causes of credit risk were analyzed, this stage is important, because it helps to identify ways to overcome threats to a specific institution or in general system, and also minimizes the likelihood of risks. In the course of the research, the issue of non-performing loans was considered, this is an integral category of the bank lending process. A low-quality loan portfolio is characterized by a high proportion of non- performing loans, which is negative and requires immediate reduction. Control of their value allows to prevent serious problems of the bank's financial condition, contributes to improving the stability of both a specific institution and the banking system in general. In addition, the amount of reserves for outstanding liabilities was analyzed, the amount of reserved funds characterizes the credit risk management process. When implementing credit activities, it is important to comply with the economic standards of the National Bank of Ukraine, which provide an opportunity to analyze the accepted credit risk from a different perspective. That is why the dynamics of these indicators during 2018-2022 were considered, where special attention was paid to the group of credit risk indicators.

Stimulators of Credit Activity of Banking Institutions

The functioning of the banking system, in the face of financial and economic shocks, is gaining global scale, and requires banking institutions to guarantee financial stability. The aim of the article is to consider the regulators of credit activity of banking institutions in the interbank market and the debt obligations of Ukrainian borrowers. A comprehensive methodological approach to assessing the stimulators of credit activity of banking institutions, which allows to model macroeconomic and local factors of credit risks of borrowers, scenarios for servicing their debt, given the safe level of profitability, liquidity in the interbank market in the current period is implemented. A comprehensive methodological approach to assessing the stimulators of credit activity of banking institutions on the basis of cognitive analysis and modeling of factors of the banking system, which are determined by stress testing when the exchange rate is changing. Interest rate fluctuations in the interbank market and liquidity in the country is proposed. The model of a complex assessment by a banking institution of the credit risk of a debtor-financial company when servicing its debt on the interbank market is presented. The cognitive analysis is carried out and the cognitive map of stimulators of crediting of the economy of Ukraine by banking institutions is constructed. Optimistic and pessimistic scenarios for changes in the lending activity of the banking system were identified, the growth of loans to residents was chosen as a desirable situation, taking into account the impact of inflation and devaluation of the hryvnia, as well as the growth index of the banking system. The integrated indicator of creditworthiness of borrowers and the relationship between quantitative and qualitative indicators of credit risk with a factor load on debt service by financial companies of Ukraine are calculated.

An Evaluation of Credit Risk Management and its Impact on the Financial Performance: Evidence from the Banking Sector of Pakistan

The purpose of the study is to examine the impact of credit risk on the financial performance of the banking sector and make a comparison among different banks in Pakistan. The study used panel regression as an underlying mechanism to determine the link between credit risk indicators and profitability determinants. The data of 23 banks for a period of 2006-2019 have collected from the annual report of the State Bank of Pakistan (SBP). The study mainly relies on the private vs. pubic and Islamic vs. conventional banking sector, the data were analyzed by using E-views software The results found that the independent variable capital adequacy has an insignificant impact on the financial performance of the baking sector. The other indicators of credit risk like the non-performing loan ratio, loan loss provision ratio, and leverage ratio have a significant relationship with the financial performance of banks in Pakistan. The study findings aim to contribute its part positively and it will surely help the bank managers, and investors to identify the risk and enhance the performance by paying more attention towards it and to generate improved policies to govern their institutions by mitigating the risk

Analysis of Credit Risk and its Impact on Financial Soundness - Analytical Study of the Bank of Baghdad in Iraq for the Period (2005-2019(

This research aims to study the effect of credit risk on financial soundness , The Bank of Baghdad was chosen in the city of Baghdad, which is one of the largest private commercial banks in Iraq , In addition, the bank has a presence in the Middle East and North Africa and consists of (7) partner banks (Bank of Baghdad in Iraq, Bank of Syria and the Gulf in Syria, Gulf Bank Algeria in Algeria, Jordan Kuwait Bank in Jordan, Tunis International Bank in Tunisia, Burgan Bank. In Kuwait, United Gulf Bank in Bahrain). The time period for the search was for annual data from 2005 to 2019. The research started from a problem (Is there an impact of credit risk on financial safety indicators?) Due to its great impact on the success of banking activity. In order to analyze the effect, the SPSS statistical package program was used according to the simple linear regression method, The most important conclusions were reached, the presence of a statistically significant effect between credit risk indicators and financial soundness indicators, with the exception of the loan-to-assets ratio on the profitability index, because the level of significance (9.5%) is higher than the acceptable level (5%).

A measure of Turkey's sovereign and banking sector credit risk: Asset swap spreads

The existence of the credit derivatives written on the eurobonds such as credit default swaps or asset swaps allows policymakers and investors to monitor the evolvement of credit risk. However, these instruments are mostly available in advanced economies, whereas the market for credit derivatives in emerging market countries, including Turkey, is limited in terms of liquidity and maturity. In this regard, this study aims to construct a proxy for the credit risk of the Turkish Treasury and banking sector in international markets by calculating asset swap spread for US dollar-denominated fixed coupon eurobonds, which requires a robust estimation of the relevant yield curves. The study firstly presents the estimation of the sovereign and banking sector yield curves and then constructs a synthetic asset swap structure to obtain embedded credit risk premia in the eurobond curves. Our findings show that the proposed credit risk indicator is vastly correlated with credit default swap premium. In addition to this, estimated eurobond curves are also useful for monitoring borrowing cost dynamics of the Turkish Treasury and banking sector in international markets.

Network tail risk estimation in the European banking system

Measuring interconnectedness in a banking system to identify the potential transmission channels of systemic risk is a main issue for the analysis of financial stability. We develop a methodology based on conditional tail risk networks to assess the channels of transmission in a banking system and to identify the most relevant and/or fragile institutions. The networks are constructed using quantile graphical models and the proposed framework can be considered as a network extension of the ΔCoVaR approach by Adrian and Brunnermeier (2016). From the conditional tail risk networks we can then compute synthetic indices of systemic risk for each bank. An additional set of systemic risk indicators is computed by considering together the network of conditional tail risk and bank-specific indicators of credit risk (as an example we use the ratio of non-performing loans, NPL). The empirical analysis focuses on the European banking system and considers a panel of 36 representative banks. Among the main findings, we found evidence of regional clusters of interconnected banks, especially in crisis period. Moreover, in terms of interconnectedness alone, systemic risk is diffused relatively evenly across European banks, while the set of systemic indicators built using also NPL highlighted a concentration of risk in southern European countries.