scholarly journals Collateral sufficiency as an adapt financial covenant in bank crediting

2021 ◽  
Vol 26 (1) ◽  
pp. 83-106
Author(s):  
Aleksandr M. KARMINSKII ◽  
Ol'ga D. KHON
Keyword(s):  
Credit Risk ◽  
Three Dimensions ◽  
Probability Of Default ◽  
Russian Market ◽  
New Approach ◽  
Credit Risks ◽  
Econometric Methods ◽  
Psychological Risk ◽  
The Impact ◽  
Linear Regressions

Subject. The article examines the Loan-to-Value ratio in three dimensions. First, as a measure of leverage, helpful to understand the spread of systemic risk in the economy. Second, we identify LTV throughout financial covenants. Finally, we implement LTV to indicate the probability of default. Objectives. The goal of the paper is to study the impact of collateral sufficiency on credit risk throughout adjusted financial covenants for bank corporate loans. Methods. To conduct the research, the authors implement econometric methods, linear regressions and binary models. Results. We have revealed the prevalence of the posterior theory of the impact of the collateral sufficiency on the credit risk evaluation by corporate loans. We have also revealed that the higher credit risks, the higher collateral requirements to pledge the loans. Conclusions and Relevance. We have considered a new approach to identify collateral requirements, throughout LTV measures, as adjusted financial covenants on the Russian market. Lender’s preferences are being stronger at the time of downturns in economic activity. At the same time, economic growth neutralizes any visible behavioral favors/patterns. Hereby psychological risk components are quite essential, and need studying in modern banking.

scholarly journals Methods of Calculation of Expected Credit Losses Under Requirements of IFRS 9

2019 ◽  
Vol 13 (4) ◽  
pp. 74-86
Author(s):  
Alfiya Vasilyeva ◽  
Elvina Frolova
Keyword(s):  
Credit Risk ◽  
Financial Reporting ◽  
Time Lag ◽  
Reporting Standard ◽  
International Financial Reporting Standard ◽  
Macroeconomic Factors ◽  
Credit Risks ◽  
Ifrs 9 ◽  
The Impact ◽  
Credit Losses

The most important area of work for financial market regulators including International Accounting Standards Board is to clarify the metrics of credit assessment. This problem became particularly relevant after the financial crisis of 2008, when the insolvency of approaches to the assessment of credit risks adopted under the then international financial reporting standard IFRS (IAS) 39 became apparent, since credit losses on financial instruments were taken into account by the “loss model”, and therefore, the asset was recognized as financially impaired due to the fact of credit quality deterioration and significant time lag. From 1 January 2018 of a new international financial reporting standard IFRS9 IFRS 9 is based on a different approach — the principle of “expected credit losses” (ECL). The transition to IFRS 9 is intended to strengthen the banking system by increasing reserves , the banking system’s stability can be increased also. The new business model radically changes the approach to the formation of reserves, including by taking into account the impact of macroeconomic indicators on their value. According to various estimates, the scale of increase in reserves ranges from 30% to 50%. The purpose of this article is to systematize the methodological principles and approaches that underlie the requirements of IFRS 9 (basic and simplified and POCI approaches), as well as a comparison of the main methods for assessing the probability of default and expected credit losses (Weibul distribution, migration matrix, generator matrix ) In the framework of this article, the authors formulated criteria for the transfer of assets between the stages of credit risk (stage), and also formulated the principles for calculating expected credit risks for each stage, taking into account macroeconomic factors. This article is of practical value, as it can be the basis for the development of methods for calculating the expected credit risks of corporate clients of commercial banks, and can also be used to improve credit risk management models.

The Credit Securitisation Process as a Tool of Portfolio Credit Risk Managing

2012 ◽  
pp. 5-28
Author(s):  
Di Clemente Annalisa
Keyword(s):  
Credit Risk ◽  
Simulation Analysis ◽  
Risk Mitigation ◽  
Probability Of Default ◽  
Loan Portfolio ◽  
Asset Return ◽  
Portfolio Credit Risk ◽  
The Impact ◽  
Monte Carlo Simulation Model

This study explores the role of the credit securitisation process in managing the credit risk amount of the banking loan portfolio, when the bank originator retains a residual equitylike class as illiquid first loss position (FLP). An Importance Sampling Monte Carlo simulation model has been implemented for estimating the portfolio credit risk amount, taking into account the portfolio credit risk mitigation effect provided by the credit securitisation process. This study identifies the credit asset pool able to produce the larger effect of credit risk reduction on the loan portfolio, when the asset pool is unloaded off the banking book. Moreover, this simulation analysis quantifies the extent of the portfolio credit risk mitigation, produced by the securitisation process of the asset pool previously identified. The impact of the securitisation activity has been also investigated when the probability of default and the asset return correlation of the obligors in portfolio are changing.

scholarly journals Increase of banks’ credit risks forecasting power by the usage of the set of alternative models

2018 ◽  
Vol 4 (2) ◽  
pp. 155-174
Author(s):  
Alexander M. Karminsky ◽  
Ella Khromova
Keyword(s):  
Credit Risk ◽  
Probability Of Default ◽  
Risk Models ◽  
Alternative Models ◽  
Default Model ◽  
Optimal Weights ◽  
Credit Risks ◽  
Rating Model ◽  
Synergic Model

The paper is aimed at comparing the divergence of existing credit risk models and creating a synergic model with superior forecasting power based on a rating model and probability of default model of Russian banks. The paper demonstrates that rating models, if applied alone, tend to overestimate an instability of a bank, whereas probability of default models give underestimated results. As a result of the assigning of optimal weights and monotonic transformations to these models, the new synergic model of banks’ credit risks with higher forecasting power (predicted 44% of precise estimates) was obtained.

scholarly journals On Credit Risk Contagion of Supply Chain Finance under COVID-19

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Wentao Chen ◽  
Zhenlin Li ◽  
Zhuoxin Xiao
Keyword(s):  
Supply Chain ◽  
Steady State ◽  
Credit Risk ◽  
Network Size ◽  
External Shocks ◽  
Credit Risks ◽  
Supply Chain Finance ◽  
Huge Impact ◽  
Credit Risk Contagion ◽  
The Impact

Existing research on credit risk contagion of supply chain finance pays more attention to the influence of network internal structure on the process of risk contagion. The spread of COVID-19 has had a huge impact on the supply chain, with a large number of enterprises experiencing difficulties in operation, resulting in increased credit risks in supply chain finance. Under the impact of the epidemic, this paper explores the transmission speed and steady state of credit risk when the supply chain finance network is affected by external impact so that we can have a more complete understanding of the ability of supply chain finance to resist risks. The simulation results show that external shocks of different degrees will increase the number of initial infected enterprises and lead to the increase in credit risk contagion speed but have no significant impact on network steady state; the speed of credit risk contagion is positively correlated with network complexity but not significantly affected by network size; core enterprises infected will increase the rate of credit risk contagion. The intensity of policy intervention has obvious curative effect on the risk caused by external shock. When the supply chain financial network is affected by external shocks, the intensity, time, and pertinence of policy response can effectively prevent the credit risk contagion.

scholarly journals The NBU Economic Standards as an Instrument for Regulating the Banking Activities

2021 ◽  
Vol 3 (518) ◽  
pp. 119-126
Author(s):  
L. V. Sus ◽  
◽  
Y. Y. Sus ◽  
Keyword(s):  
Credit Risk ◽  
Commercial Banks ◽  
Banking System ◽  
Banking Supervision ◽  
Correlation And Regression Analysis ◽  
Basel Committee ◽  
Credit Risks ◽  
Banking Institutions ◽  
Banking Institution ◽  
The Impact

Researching the problems of banking supervision in the course of the policy of cleaning the banking system of Ukraine is of particular importance. The issues of efficiency of regulation of the activities of commercial banks with the help of economic standards of the NBU remain topical. The article is aimed at a theoretical-methodical substantiation of the NBU economic standards system and identifying the peculiarities of their application as instruments for regulating the banking activities. The state of compliance with capital, liquidity and credit risk standards by commercial banks of Ukraine is examined. A correlation and regression analysis of the impact of credit risk standards on the volumes of overdue credit arrears of banks is carried out. Ways to improve the system of regulation of the activities of commercial banks based on the principles developed by the Basel Committee on Banking Supervision are proposed. A further proposal is made as to introducing an additional economic standard for the regulation of credit risks, which would assess the risks of repayment of loans. In addition, it will be expedient for Ukraine to build a conceptual banking supervision, which will ensure close interaction of components in order to improve the efficiency of banking institutions. A comprehensive system of banking supervision should diagnose the level of risks and implement systems of their management at the level of each separate banking institution.

scholarly journals Stress Testing for Credit Risk Exposure in Islamic Banks

2020 ◽  
Vol 6 ◽  
pp. 1
Author(s):  
Fadwa A Mohammed ◽  
Ibrahim A Onour ◽  
◽  
Keyword(s):  
Credit Risk ◽  
Stress Testing ◽  
Banking System ◽  
Risk Exposure ◽  
Probability Of Default ◽  
Islamic Banks ◽  
Macroeconomic Variables ◽  
Credit Risks ◽  
Macroeconomic Indicators ◽  
Design Stress

In this study, we investigate the link between default loans and macroeconomic and bank-specific variables to assess exposure of Islamic banks to credit risks, and then design stress testing scenarios to assess the banking system’s resilience to adverse shocks. The results suggest that credit risk exposure of Islamic banks in Sudan is mainly affected by bank-specific variables, which include changes in total assets, total deposits, and total loans; all of them have a negative and significant impact on the probability of default loans. The study also indicates that the macroeconomic variables, which include growth of domestic product, change in exchange rate premium, and change in money supply, have positive but insignificant effects on the risk of default loans. The study concludes by pointing out that the Islamic banking system in Sudan is more vulnerable to bank-specific risk exposure rather than macroeconomic indicators.

scholarly journals Impact of ownership structure and ownership concentration on credit risk of Chinese commercial banks

2019 ◽  
Vol 16 (2) ◽  
pp. 253-272 ◽  
Author(s):  
Yang Liu ◽  
Sanjukta Brahma ◽  
Agyenim Boateng
Keyword(s):  
Credit Risk ◽  
Ownership Structure ◽  
Commercial Banks ◽  
Ownership Concentration ◽  
Private Ownership ◽  
Content Type ◽  
Credit Risks ◽  
Bank Ownership ◽  
Chinese Banks ◽  
The Impact

Purpose The purpose of this paper is to examine the effects of bank ownership structure and ownership concentration on credit risk. Design/methodology/approach Using panel data on a sample of 88 Chinese commercial banks, with 826 observations over a period of 2003–2018, this study has applied system generalised method of moments regression to examine the impact of bank ownership structure and ownership concentration on credit risk. This study has used two measures of credit risk, which are non-performing loan ratio (NPLR) and loan loss provision ratio (LLPR). Findings The results show that ownership type (both government and private ownership) exerts a positive and significant impact on credit risk. Measuring ownership concentration using Herfindahl–Hirchmann Index, the results indicate that concentration of ownership in the hands of government has a negative and significant effect on credit risk, whereas private ownership concentration positively impacts credit risk. Overall, the findings suggest that concentration of ownership in government hands reduces risk; however, private ownership concentration exacerbates credit risks. The results are invariant to both measures of credit risk, before and after the financial crisis. Practical implications The findings provide useful insight to guide policy decisions in Chinese banks’ lending policies and bank ownership. Originality/value Using two ex post measures of credit risk, NPLR and LLPR, and one ownership concentration measure, HHI, this study deepens our understanding on the effectiveness of Chinese banks’ corporate governance reforms on managing credit risks.

scholarly journals COVID-19’s influence on the credit risks and enterprise innovation of the Guangxi manufacturing——Based on the measure of KMV model

2021 ◽  
Vol 275 ◽  
pp. 03071
Author(s):  
LiJun Shen ◽  
Yu He
Keyword(s):  
Credit Risk ◽  
Manufacturing Industry ◽  
Credit Risk Management ◽  
Credit Risks ◽  
Innovation Activities ◽  
Kmv Model ◽  
Before And After ◽  
Enterprise Innovation ◽  
Index Value ◽  
The Impact

The paper used the KMV model to manufacturing industry of Guangxi in China to concretely abstract the credit risk and enterprise innovation into a measurable quantitative index, and compare the changes in credit risk before and after COVID-19. This paper selects 17 Listed Companies in Guangxi manufacturing industry as empirical samples, and calculates the expected default rate of different companies by using the traditional and modified KMV models. The larger the index value is, the higher the credit risk is, And then affect the enterprise innovation activities. The results show that the overall credit risk management ability of Guangxi’s manufacturing industry is relatively high, but by the impact of COVID-19, credit risk has increased. If left unguarded, it will have an impact on enterprise innovation.

scholarly journals The Impact Of PD-LGD Correlation On Expected Loss And Economic Capital

2017 ◽  
Vol 16 (3) ◽  
pp. 157-170 ◽  
Author(s):  
Gary Van Vuuren ◽  
Riaan De Jongh ◽  
Tanja Verster
Keyword(s):  
Credit Risk ◽  
Real Time ◽  
Economic Capital ◽  
Probability Of Default ◽  
Expected Loss ◽  
Loan Portfolio ◽  
Correlation Dependence ◽  
Loss Given Default ◽  
Default Data ◽  
The Impact

The Basel regulatory credit risk rules for expected losses require banks use downturn loss given default (LGD) estimates because the correlation between the probability of default (PD) and LGD is not captured, even though this has been repeatedly demonstrated by empirical research. A model is examined which captures this correlation using empirically-observed default frequencies and simulated LGD and default data of a loan portfolio. The model is tested under various conditions dictated by input parameters. Having established an estimate of the impact on expected losses, it is speculated that the model be calibrated using banks' own loss data to compensate for the omission of correlation dependence. Because the model relies on observed default frequencies, it could be used to adapt in real time, forcing provisions to be dynamically allocated.

The Impact of COVID-19 on Supply Chain Credit Risk

2020 ◽  
Author(s):  
Senay Agca ◽  
John R. Birge ◽  
Zi'ang Wang ◽  
Jing Wu
Keyword(s):  
Supply Chain ◽  
Credit Risk ◽  
The Impact
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