Data Driven Design to Credit Risk Management Using Digital Footprint Intelligence

Author(s):  
Ekaterina V. Orlova
2012 ◽  
Vol 3 (8) ◽  
pp. 31-37
Author(s):  
Nayan J. Nayan J. ◽  
◽  
Dr. M. Kumaraswamy Dr. M. Kumaraswamy

2021 ◽  
Vol 14 (5) ◽  
pp. 211
Author(s):  
Iryna Yanenkova ◽  
Yuliia Nehoda ◽  
Svetlana Drobyazko ◽  
Andrii Zavhorodnii ◽  
Lyudmyla Berezovska

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.


Author(s):  
Abu Hanifa Md. Noman ◽  
Md. Amzad Hossain ◽  
Sajeda Pervin

Objective - The study aims to investigate credit risk management practices and credit risk management strategies of the local private commercial banks in Bangladesh. Methodology -The investigation is conducted based on primary data collected from a set of both closed end and open end questionnaire from 23 out of 39 local private commercial banks in Bangladesh. Descriptive statistics has been used in processing the data and interpreting the results. Findings - The results reveal that credit risk management practice of the sample banks is sound which is attributed to the appropriate implementation of Basel II and credit risk management guidelines the country's central bank. The findings further show that use of Credit risk grading is most popular and effective criteria for measuring the borrowing capacity of the borrowers. In order to control credit risk and preventing losses from credit exposure banks give more focus on collateralization, accurate loan pricing and third party guarantee. Loan is monitored properly and credit reminder is given to the client if principal and interest remain outstanding for three months. The study further reveals that lack of experienced and trained credit officers, lack of genuine market information and Lack of awareness regarding non-genuine borrower are the most important problems of current credit risk management practices in Bangladesh. Novelty - To the best of the knowledge of the authors the study is the first that investigates credit risk management strategies of private commercial banks, especially on Bangladesh. Type of Paper - Empirical Keyword : Bangladesh; Commercial Bank; Credit risk; Credit risk management; Credit risk management strategies.


Author(s):  
Xiang Zou ◽  
Jinting Zhao ◽  
Yun Tong

This paper focuses on the construction of college students' credit evaluation system and credit risk management under the background of big data. Firstly, based on the 5C approach, this paper evaluates the personal credit of college students from 5 dimensions and 24 indicators, which finally contribute to the establishment of the credit evaluation system for college students. Then, the partial least squares method is used to build the structural equation model to evaluate the effectiveness of the credit evaluation system for college students. According to the in-depth analysis of PSL-SEM, the factors that affect the credit risk of college students are effectively evaluated, and it has contributed to the establishment and improvement of the credit system of college students. Keywords: Personal Credit, Credit Evaluation, Credit Risk, 5C Approach, PLS-SEM.


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