Credit Risk Indicators Research Articles

Financial Risk Assessment: Case of „Lietuvos Geležinkeliai“, AB

Abstract This research paper focuses on the analysis of the financial risk of Lietuvos geležinkeliai, AB (eng. Lithuanian Railways), which activities are passenger and freight transportation by rail. In order to assess the financial risk of the leading company areas of financial risk were identified and are as follows: liquidity risk, credit risk and market risk. However, due to limited access to statistics only financial report of the organisation were analysed and, hence, just liquidity and credit risk were investigated. Consequently, the limitation of the current research is that only two categories of financial risk were analysed. For the purpose of financial risk analysis, the key indicators of liquidity and credit risk were distinguished from the literature. The results showed that the biggest problem of the company is too small short-term assets and the profitability indicators, which were strongly influenced by net profit (loss).

CREDIT CAPACITY ASSESSMENT OF COMMERCIAL BANK BORROWER

The purpose of the article is to study the essence of solvency of the enterprise, to determine the approaches to assessment and analysis of solvency. Since the assessment of the borrower's solvency is the key to the successful functioning not only of the financial and credit institution, but also of the enterprise itself, so in the conditions of formation and development of market relations lenders need to have an accurate idea of the borrower's solvency. Relevance of the research topic is explained by the fact that today the solvency of the enterprise requires a thorough and comprehensive research in terms of the solvency of enterprises and the development of a scientific justification for a common algorithm that borrowers can use to calculate their credit obligations. Today, there is no single algorithm for determining a borrower's solvency. Each banking institution uses its own methodology, which, in its opinion, is the most effective and takes into account a wide range of financial indicators. According to the valuation specificity for the assessment of legal entities regulated by the NBU, determining the borrower's solvency involves analyzing its financial and economic characteristics Requirements of the Regulations on the determination of the size of credit risk by the banks of Ukraine established the calculation of the credit risk indicator, which provides for the definition of the integral indicator, calculation of the borrower's financial class and the probability of default. Within the limits of the given research the complex estimation of Technologia JSC solvency has been carried out, by results of which the quantitative indicators received as a result of construction of the integral model, are included into the range of values corresponding to the second class of the borrower. Calculation of the overall qualitative indicator confirmed the high level of solvency of the studied enterprise, with a minimum probability of default. In order to improve the quality of the solvency assessment of the borrower we propose, in further studies, to consider the competitiveness of the enterprise as a factor of more accurate determination of its financial condition and solvency. Keywords: solvency, borrower, financial standing, financial factors.

Credit Risk Management Effectiveness Assessment on the Basis of Information from the Bureau of Credit Histories

The approaches of assessing the effectiveness of credit risk management are investigated. Two conceptual approaches are proposed for evaluation of efficiency. The first approach is based on using the benchmark, which is formed on the basis of a special set of credit risk indicators. The values of benchmark indicators are calculated on the basis of the Bureau of credit histories data. They represent, in a certain sense, average market values. The set of indicators includes the parameters of the borrower’s inflow and the indicators of loan portfolio delinquency. As an integral measure of risk management effectiveness for some lender, a special indicator is considered. This is an upper semi-quadratic deviation of the lender’s values from the benchmark`s values.The second approach of assessing the effectiveness is based on the audit of rejection correctness. The Credit bureau information allows analyzing borrowers that were rejected and the presence / absence of delinquency for new received loans. The rejected applications should be classified in two classes. The first class contains applications rejected on the basis of verification rules and procedures. The indicator of efficiency here is the level of incorrectly rejected loan applications. The second class includes applications rejected on the basis of the lender`s internal application scoring. The tool for scoring improvement is the re-calibration of weights. It is based on calculations of information values of scoring indicators on a consolidated creditor database and the Credit history bureau data of the rejected applications.The implementation of the proposed evaluation system depends on the degree of development of the Credit history bureau institution and the specifics of its functioning. The greatest effect is achieved in the case of transferring the full information from creditors to the Credit bureau and information exchange between bureaus.Article received 01.05.2018

An analysis through credit default swap, asset swap and zero-volatility spreads: Coup attempt and Bist 100 volatility

In this study, we explore the volatility structure of BIST 100 index returns through Markov Regime Switching VAR model in the domain of credit risk indicators of Turkey. Also, July 2016 coup attempt has been added to the model, to examine its impact on the volatility. According to the results, Asset Swap spread displays better performance than other two credit risk indicators in signaling. Markov Regime Switching results demonstrate that while BIST 100 return volatility is not affected by credit risk in low volatility regime, in high volatility regime, CDS, ASW and ZV spreads have a significant impact on the volatility. This effect, however, can be omitted due to its very low coefficient. Finally, it is seen that July 2016 coup attempt and following operations did not cause any increase in BIST 100 return volatility.

Determinants of Commercial Banks' Profitability. Evidence from Hungary

This paper aims to find out whether bank‑specific (internal) factors impact on the profitability of commercial banks in Hungary for 16 a year period ranging from 2000–2015. The study employs a sample of twenty‑six commercial banks with four hundred sixteen observations. The study employs return on average assets (ROAA) as a proxy for bank profitability, and it also considers bank‑specific (internal) factors as independent variables. These include asset quality (non‑performing loans), overhead costs, bank size, net interest margin, and liquidity risk plus capital adequacy ratio. The study uses panel regressions, descriptive statistics and correlation analysis for the investigations. The panel regression models are to estimate the impact of bank‑specific (internal) factors on bank profitability. The Hausman specification test was conducted on the panel regression models in order to identify the best and appropriate model for the study. The empirical findings reveal that non‑performing loans, overhead costs and liquidity had a significant negative impact on bank profitability as bank size had a significant positive impact on profitability. However, net interest margin and capital adequacy ratio had no impact on bank profitability. The study concludes that bank size and asset quality are bank‑specific factors that have the biggest impact on commercial banks’ profitability in Hungary for the period under investigation. The study recommends that commercial banks should endeavor to manage and reduce overhead costs to be able to earn more profits since overhead costs adversely affect bank profitability. More so, commercial banks’ managers should regularly monitor credit and liquidity risk indicators as well as pursuing diversification policies of income sources while upholding optimisation of operational costs.

Risk Framework Analysis in the Management of Sovereign Debt: The Argentine Case

The main objective of this paper is to develop a practical approach to Argentina’s sovereign risk management. Through Contingent Claim Analysis (CCA), Gape, Gray, Lim and Xiao (2008)[1] developed a sovereign risk framework whereby we can construct a marked to market sovereign balance sheet and obtain a set of credit risk indicators that can help policy-makers: set thresholds for foreign reserves, design risk mitigation strategies and select best policy options. The main contribution is that instead of using a conventional index such as GBI-EM1 in order to estimate the volatility of domestic currency liabilities, we use 24 sovereign domestic currency bonds to construct an interest rate covariance matrix. That is, an interest rate sensitive sovereign portfolio, whose risk factor variations2 are represented by a vector of the portfolio PV01 (present value of a basis point change) with respect to each interest rate of the zero-coupon yield curve. Since zero-coupon rates are rarely directly observable, we must estimate them from market data. In this paper we implemented a widely-used parametric term structure estimation method called Nelson and Siegel. For Argentina we generated two yield curves, i.e., sets of fixed maturity interest rates determined by Badlar and CER.

ASSESSMENT OF CREDIT RISK IN NEPALI COMMERCIAL BANKS

The main objective of the study is to identify the major indicators of credit risk among the Nepali commercial banks. The study is conducted using the sample of 15 commercial banks operated in Nepali economy. One way Fixed Effect Model (FEM) of panel data analysis is used as a major tool of analysis. All the data for the study were obtained from the database of Nepal Rastra Bank for bank specific variables and database of World Bank for macroeconomic variables for the year 2002/03 to 2014/15. The credit risk among the commercial banks in Nepal was regressed on bank specific variables such as liquidity, capital adequacy ratio, bank size, and interest spread. Similarly, the effects of macro-economic variables such as GDP growth, rate of inflation and interbank interest rate were also examined along with bank specific variables in identifying credit risk in Nepali commercial banks. The study reveals that liquidity has the significant positive impact on credit risk in Nepali commercial banks. In contrast, capital adequacy ratio and interest spread have the significant negative impact on credit risk. The analysis further confirmed that bank size and interest spread both have no any clear direction of impact on credit risk. Moving towards the GDP growth, credit risk in Nepali commercial banks is negatively fluctuates with GDP growth, however, the statistics show the coefficients are insignificant at 5% level. Contrarily, Inter-bank interest rate has insignificant negative impact on credit risk in Nepali commercial banks.

Sovereign credit default swap spreads as tools of ensuring the international financial security of the Eurozone countries

The article investigates the state of the Eurozone countries’ financial security in the context of the world economic environment globalization. For the purpose of this, financial security is considered in terms of institutional, instrumental, and interdisciplinary dimensions. The subject of research is the tools of the Eurozone countries’ financial security ensuring. The goal is to research the dependence of the financial activity of the euro area countries on the results of credit rating assessments by rating agencies using the credit default swap instrument in the context of the Eurozone countries’ financial security ensuring.The objective is the process of the Eurozone countries’ financial security ensuring in the context of the world economic environment globalization. General scientific methods are used, such as system analysis – to determine the peculiarities of the financial security ensuring,regression analysis - to determine the relationship between the spreads of sovereign credit default swaps and the eurozone credit rating class. The following results are obtained: on the basis of the regression analysis of the spreads of sovereign credit default swaps and the eurozone credit rating classindicators the influence of sovereign credit risk figure on investment attractiveness of the Eurozone countries is determined; the approaches of the credit default swaps usage in the context of the researching of the credit rating impact on the investment attractiveness of the sovereigns are systematized; examination of dependence between credit ratings and sovereign credit default swap spreads is applied as the main research tool. Conclusions: for the sake of the Eurozone countries’ financial security enhancement, the authors offer replacement of the credit ratings of leading credit rating agencies with alternative credit risk indicators : market assessments of credit risk, instruments for internal credit risk assessment and third party valuation, as well as the ways of strengthening the Eurozone’s financial security through the establishment of permanent threat monitoring system and estimation of their quantity and quality variables are suggested in the article.

Assessing sovereign default risk: A bottom-up approach

This study assesses sovereign default risk of individual U.S. states utilizing information about default risk at the company level. We link integrated risk factors of the private sector to the overall sovereign risk of state governments in conjunction with additional financial variables. Using data on Moody’s KMV expected default frequencies (EDFs) on corporate default risk, we derive credit risk indicators for different industries. Building on these measures, we then develop state level credit risk indicators encompassing industry compositions to explain the behaviour of credit default swap (CDS) spreads for individual states. We find that market-based measures of private sector credit risk are strongly associated with subsequent shifts in sovereign credit risk premiums, as measured by CDS spreads. The developed credit risk indicators are highly significant in forecasting sovereign CDS spreads at weekly and monthly sampling frequencies. Overall, our findings suggest a strong predictive link between market expectations of private sector credit quality and expectations of sovereign credit quality - a connection that is not directly discernible from scoring models.

Credit risk in banks’ exposures to non‐financial firms

AbstractThis paper outlines a framework based on microdata and a structural model to gauge credit risk in banks’ exposures to non‐financial firms. Sectoral risk factors are accounted for using a multi‐factor model. We use expected and unexpected losses as indicators of credit risk stemming from the corporate sector as a whole, and we put forward a measure of systemic risk relevance of economic sectors. We apply the model to the Italian economy, showing the sensitivity of credit risk indicators to different characteristics of default risk, cyclicality and concentration of economic sectors.

Credit Ratings and Credit Risk: Is One Measure Enough?

This paper investigates the information in corporate credit ratings. If ratings are to be informative indicators of credit risk, they must reflect what a risk-averse investor cares about: both raw default probability and systematic risk. We find that ratings are relatively inaccurate measures of raw default probability—they are dominated as predictors of failure by a simple model based on publicly available financial information. However, ratings do contain relevant information since they are related to a measure of exposure to common (and undiversifiable) variation in default probability (“failure beta”). Systematic risk is shown to be related to joint default probabilities in the context of the Merton [Merton RC (1974) On the pricing of corporate debt: The risk structure of interest rates. J. Finance 29(2):449–470] model. Empirically, it is related to credit default swap spreads and risk premia. Given the multidimensional nature of credit risk, it is not possible for one measure to capture all the relevant information. This paper was accepted by Gustavo Manso, finance.

Analysing Cross-Currency Basis Spreads

This paper investigates the drivers of cross-currency basis spreads, which were historically close to zero but have widened significantly since the start of the financial crisis. Credit and liquidity risk, as well as supply and demand have often been cited as general factors driving cross-currency basis spreads, however, these spreads may widen beyond what is normally explained by such variables. We suggest market proxies for EUR/USD basis swap spread drivers and build a multiple regression and cointegration model to explain their significance during three different historical periods of basis widening. The most important drivers of the cross-currency basis spreads appear to be short- and medium-term EU financial sector credit risk indicators, and to a slightly lesser extent, short- and medium-term US financial sector credit risk indicators. Another important driver is market volatility for the short-end basis spread, and the EUR/USD exchange rate for the medium term basis spread, and to a lesser extent, the Fed/ECB balance sheet ratio.

An improved SMO algorithm for financial credit risk assessment – Evidence from China’s banking

With rapid development of financial services and products, credit risk assessment has recently gained considerable attention in the field of financial risk management. In this paper, an improved credit risk assessment approach is presented. Based on the credit data from China Banking Regulatory Commission (CBRC), a multi-dimensional and multi-level credit risk indicator system is constructed. In particular, we present an improved sequential minimal optimization (SMO) learning algorithm, named four-variable SMO (FV-SMO), for credit risk classification model. At each iteration, it jointly selects four variables into the working set and an theorem is proposed to guarantee the analytical solution of sub-problem. The assessment is made on China credit dataset and two benchmark credit datasets from UCI database and CD-ROM database. Experimental results demonstrate FV-SMO is competitive in saving the computational cost and outperforms other five state-of-the-art classification methods in credit risk assessment accuracy.

Investigating the relationship between credit risk indicators and timely fulfillment of the customers' obligations (a case study of bank sepah branches in east Azerbaijan and Ardabil regions)

This research was conducted with the aim to investigate and identify the relationship between credit risk indicators and timely fulfillment of the legal customers’ obligations of Sepah Bank. To do this, credit data and financial ratios of 370 cases of Sepah’s Bank legal customers who had used credit services of Sepah Bank branches in East Azerbaijan and Ardabil regions during a period from 2012-2014 were collected. In this respect, data related to 27 financial ratios as explanatory variables of 370 cases of the mentioned sample were extracted from their credit files and were selected to be tested after performing required refinement and classifying in two groups of extracted data from audited and unaudited financial statements. Then the relationships between these variables and timely fulfillment of obligations were investigated using logistic regression method and considering the significance of the independent variables at 95% confidence level. The results of the research showed that accounting, current, and acid test ratios, working capital, return on total assets, return on equity and gross profit to sell listed in unaudited financial statements group and current ratio/ liquidity ratio, current assets ratio, accounts receivable turnover ratio, return on total assets, debt-to-equity ratio, debt to asset ratio, current debts to equity ratio listed in audited financial statements group have a significant relationship with timely fulfillment of the customers' obligations.

Islamic banking and risk: The impact of Basel II

The expansion of Islamic banking raises questions about its impact on financial stability. We question whether the implementation of Basel II standards influences the gap in risk between Islamic and conventional banks. We use a sample of 558 banks from 24 countries that had an Islamic banking presence between 2007 and 2013. We exploit the variation in Basel II implementation across countries to use a differences-in-differences approach. Risk is considered according to insolvency risk and credit risk indicators. We find that Basel II standards enlarge the gap in risk between Islamic and conventional banks at the expense of Islamic banks. These findings are also observed when separately considering small banks and large banks. We thus support the view that the relationship between Islamic banking and risk is conditional to the regulatory framework.

A STUDY ON THE IMPACT OF CREDIT RISK ON THE PROFITABILITY OF STATE BANK OF INDIA (SBI)

The study is aimed at investigating the impact of Credit risk on the profitability of the bank. Through extensive literature review, various factors that influence Credit risk are identified as Capital adequacy ratio (CAR), Nonperforming Asset ratio (NPA), Loan to Deposit Ratio (LDR), Cost per Loan Ratio (CLR), Provision Coverage Ratio (PCR), Leverage Ratio (LR), and Nonperforming Asset to Asset Ratio (NPAAR). Return on Equity (ROE) is identified as the indicator of profitability. The secondary data is collected from the Annual reports of the State Bank of India for twenty years (1997-2016). The data is analysed using multiple regression. The result showed that NPAAR alone have significant negative impact on ROE and other indicators of credit risk do not have significant impact on ROE. But overall credit risk has significant impact on profitability of State Bank of India. State bank of India faces credit risk due to inefficient Credit risk management. So it is advised to improve Credit risk management practices in State Bank of India. State Bank of India can minimise the Credit risk by reducing the Nonperforming assets by framing strict loan policies.

Credit Risk in the Euro Area

We construct credit risk indicators for euro area banks and non‐financial corporations. These indicators reveal that the financial crisis of 2008 dramatically increased the cost of market funding for both banks and non‐financial firms. In contrast, the prior recession following the 2000 US dot‐com bust led to widening credit spreads of non‐financial firms but had no effect on the credit spreads of financial firms. The 2008 financial crisis also led to a systematic divergence in credit spreads for financial firms across national boundaries. Credit spreads provide substantial predictive content for real activity and lending measures for the euro area as a whole and for individual countries.

Assessing individual credit risk on the basis of discriminant analysis by Poland's cooperative banks

The main objective of the study was to determine the potential of Poland's cooperative banks utilising discriminant analysis to assess individual credit capability. In the construction of the scoring model, data from retail co-op bank clientele was used. The chosen banks operated in rural areas and their clients were granted loans during the years 2010-2014. The realised study considered the possibility of applying discriminant analysis to restrict a co-op bank's individual credit risk exposure. From among 28 explanatory variables describing a bank's clients who were applying for loans, five variables were found to be effective in the model: applicant's age, applicant's higher education, current loan obligations, applicant's default on loan payment, and maximum number of days an applicant was late in due payment. These variables, connected with assessing regressive coefficients returned a highly effective credit risk indicator identifying potentially insolvent clients.

English

Based on simulations of implied values for credit worthiness over a period of 5 years for 1000 consumers, the study shows robustness of the Semi-Markovian models in forecasting Probabilities of Default and Loss Given Default for a portfolio of consumer loans. The study models credit risk as a reliability problem on the basis of which we generate credit risk indicators and quantify prospective capital holding based on forecast delinquencies. Consumer ratings are based on Monte-Carlo simulation techniques and the initial probability transition matrix on the Merton model. Banks could espouse the study results to fulfill regulatory credit risk capital requirements for consumer loans.   Key words: Semi-Markov models, credit risk, Central Bank of Kenya.

The impact of credit risk management on the banking profitability: A Survey of the Theoretical and Empirical Literature

Banks as financial intermediation institutions are defined as businesses that receive and manage various risks. Among numerous banking risks, credit risk is identified by most researchers as the greatest risk affecting the performance of the bank. On the other hand, banking sector profitability has received great attention in recent years. The purpose of this paper is to recognize us with theoretical and empirical literature about the relationship that exists between credit management risk and banking profitability indicators. The most studies in this field have concluded that credit risk management is the primary contributor on the profitability of commercial banks. But there are and those studies that have proved that the impact of credit risk management on banking profitability is negligible.