Bank credit risk management early warning and decision-making based on BP neural networks

2011 ◽  
Author(s):  
Zhi-Yuan Yu ◽  
Shu-Fang Zhao
Keyword(s):  
Neural Networks ◽  
Decision Making ◽  
Risk Management ◽  
Credit Risk ◽  
Early Warning ◽  
Bank Credit ◽  
Bp Neural Networks ◽  
Credit Risk Management

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.

scholarly journals Enterprise Credit Risk Management Using Multicriteria Decision-Making

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Wenjuan Liu
Keyword(s):  
Decision Making ◽  
Risk Management ◽  
Credit Risk ◽  
Multicriteria Decision Making ◽  
Final Decision ◽  
Credit Risk Management ◽  
Multicriteria Decision ◽  
Risk Manager ◽  
Enterprise Credit ◽  
Weight Calculation

The purpose of this study is to reduce the rate of multicriteria decision-making (MCDA) errors in credit risk management and to weaken the influence of different attitudes of enterprise managers on the final decision when facing credit risk. First, several solutions that are suitable for present enterprise credit risk management are proposed according to the research of enterprise risk management in the world. Moreover, the criteria and matrix are established according to the general practice of the expert method. A decision-making method of enterprise credit risk management with trapezoidal fuzzy number as the criteria of credit risk management is proposed based on the prospect theory; then, the weight is calculated based on G1 weight calculation, G2 weight calculation method, and the method of maximizing deviation; finally, the prospect values of the alternatives calculated by each method are adopted to sort and compare the proposed solutions. Considering the difference of risk degree of managers in the face of credit risk management, the ranking results of enterprise credit risk management solutions based on three weight calculation methods are compared. The results show that as long as the quantitative value of the risk attitude of the enterprise credit risk manager meets a certain range, the final choice of credit risk management scheme ranking is consistent. This exploration provides a new research direction for enterprise credit risk management, which has reference significance.

scholarly journals Bank Credit Risk Management and Rating Migration Analysis on the Business Cycle

2014 ◽  
Vol 2 (1) ◽  
pp. 122-143 ◽  
Author(s):  
Dimitris Gavalas ◽  
Theodore Syriopoulos
Keyword(s):  
Risk Management ◽  
Business Cycle ◽  
Credit Risk ◽  
Bank Credit ◽  
Credit Risk Management ◽  
The Business Cycle ◽  
Migration Analysis

Bank Credit Risk Management and Risk Culture

2017 ◽  
pp. 321-348
Author(s):  
Doriana Cucinelli ◽  
Arturo Patarnello
Keyword(s):  
Risk Management ◽  
Credit Risk ◽  
Bank Credit ◽  
Credit Risk Management ◽  
Risk Culture

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.

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