The Relation between Bank Credit-Risk Management Procedures and Originate-to-Distribute Mortgage Quality During the Financial Crisis

2014 ◽  
Author(s):  
Gauri Bhat ◽  
Jian Cai
Keyword(s):  
Risk Management ◽  
Financial Crisis ◽  
Credit Risk ◽  
Bank Credit ◽  
Credit Risk Management ◽  
Management Procedures

scholarly journals Modeling of Bank Credit Risk Management Using the Cost Risk Model

2021 ◽  
Vol 14 (5) ◽  
pp. 211
Author(s):  
Iryna Yanenkova ◽  
Yuliia Nehoda ◽  
Svetlana Drobyazko ◽  
Andrii Zavhorodnii ◽  
Lyudmyla Berezovska
Keyword(s):  
Risk Management ◽  
Decision Support ◽  
Credit Risk ◽  
Risk Model ◽  
Bank Credit ◽  
Credit Risk Management ◽  
Loan Default ◽  
Increased Risk ◽  
Credit Portfolio ◽  
Cost Risk

This article deals with the issue of managing bank credit risk using a cost risk model. Modeling of bank credit risk management was proposed based on neural-cell technologies, which expand the possibilities of modeling complex objects and processes and provide high reliability of credit risk determination. The purpose of the article is to improve and develop methodical support and practical recommendations for reducing the level of risk based on the value-at-risk (VaR) methodology and its subsequent combination with methods of fuzzy programming and symbiotic methodical support. The model makes it possible to create decision support subsystems for nonperforming loan management based on the neuro-fuzzy approach. For this paper, economic and mathematical tools (based on the VaR methodology) were used, which made it possible to analyze and forecast the dynamics of overdue payment; assess the quality of the credit portfolio of the bank; determine possible trends in bank development. A scientific and practical approach is taken to assess and forecast the degree of credit problematicity by qualitative criteria using a mathematical model based on a fuzzy technology, which can forecast the increased risk of loan default at an early stage in the process of monitoring the loan portfolio and model forecasting changes in the degree of credit problematicity on change of indicators. A methodology is proposed for the analysis and forecasting of indicators of troubled loan debt, which should be implemented as software and included in the decision support system during the process of monitoring the risk of the bank’s credit portfolio.

Impact of Financial Crisis on Credit Risk: Pre- and Post-financial Crises 
in an Emerging Economy

2020 ◽  
Vol 9 (2) ◽  
pp. 118-132
Author(s):  
Syed Moudud-Ul-Huq ◽  
Rabaka Akter ◽  
Tanmay Biswas
Keyword(s):  
Risk Management ◽  
Financial Crisis ◽  
Credit Risk ◽  
Commercial Banks ◽  
Global Financial Crisis ◽  
Banking System ◽  
Commercial Banking ◽  
Real Economy ◽  
Credit Risk Management ◽  
The Global Financial Crisis

This aim of the article is to establish a model to discuss the reasons for changing the level of credit risk among the commercial banks of Bangladesh during the global financial crisis (GFC). Credit risk has been remaining as the essential and core risk in commercial banking activities. Multiple regression analysis is used to test the relationship among the level of credit risk as a dependent variable and financial crisis, other bank-level variables and macroeconomic variables. The causes of the GFC revealed not only systematic or structural imbalances but also the necessity to keep and strengthen the principles of credit risk management. We analyse the leading causes of the recent GFC. Moreover, the lessons that must be learnt from the weaknesses of credit risk management systems. Credit risk was found to respond to macroeconomic conditions, which indicate strong feedback effects from the banking system to the real economy. This article represents the analysis of the influence of the financial crisis on credit risk management in commercial banks and summarizes the challenges faced by banks for credit risk improvement. We hope that this reality creates new opportunities for managing credit risk in the future to increase this importance in the banks and the overall economy of Bangladesh.

Discriminant Analysis and Logistic Regression Applying To Credit Risk Management

2021 ◽  
Vol 6 (3) ◽  
Author(s):  
Ngongo Isidore ◽  
◽  
Etoua Magloire ◽  
Jimbo Claver ◽  
Mengue Mvondo Jenner ◽  
...  
Keyword(s):  
Risk Management ◽  
Logistic Regression ◽  
Discriminant Analysis ◽  
Financial Crisis ◽  
Credit Risk ◽  
Efficient Method ◽  
Credit Risk Management ◽  
Fisher Discriminant Analysis ◽  
Fisher Discriminant ◽  
The World

The financial crisis that is currently shaking the world, particularly the successive failures of the major banks have brought the issue of banking risks, including credit risk, back to the forefront. This risk must now be managed by more sophisticated methods. In this paper we present two methods that allow us to establish two functions, namely Fisher discriminant analysis and logistic regression; these two functions allow us to evaluate the risk of non-repayment incurred by a bank in the light of our data. It emerges that Fisher discriminant analysis is more effective or efficient than logistic regression for the evaluation of the risk of non-repayment of credit. Discriminant analysis and logistic regression are two methods of credit risk management here the problem we are trying to solve is how to help banks choose the most efficient method between the latter two.

scholarly journals Applying ontologies to data integration systems for bank credit risk management

2018 ◽  
Vol Special Issue on Scientific... ◽  
Author(s):  
Jalil Elhassouni ◽  
Mehdi Bazzi ◽  
Abderrahim Qadi ◽  
Mohamed Haziti
Keyword(s):  
Risk Management ◽  
Credit Risk ◽  
Bank Credit ◽  
Management Process ◽  
Credit System ◽  
Special Issue ◽  
Credit Risk Management ◽  
Integration Model ◽  
Risk Management Process ◽  
Credit Granting

Special ISSUE VSST 2016 This paper proposes an ontological integration model for credit risk management. It is based on three ontologies; one is global describing credit risk management process and two other locals, the first, describes the credit granting process, and the second presents the concepts necessary for the monitoring of credit system. This paper also presents the technique used for matching between global ontology and local ontologies.

Sign in / Sign up

Export Citation Format

Share Document