Credit Risk Management for College Students: An Analysis of Influencing Factors Based on 5C Approach

2021 ◽  
Vol 12 (1) ◽  
pp. 105-105
Author(s):  
Xiang Zou ◽  
Jinting Zhao ◽  
Yun Tong
Keyword(s):  
College Students ◽  
Risk Management ◽  
Credit Risk ◽  
Evaluation System ◽  
Least Squares Method ◽  
Credit Risk Management ◽  
Credit Evaluation ◽  
Personal Credit ◽  
Depth Analysis ◽  
Credit Evaluation System

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.

scholarly journals Big Data Credit Report in Credit Risk Management of Consumer Finance

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Lu Gao ◽  
Jian Xiao
Keyword(s):  
Risk Management ◽  
Big Data ◽  
Credit Risk ◽  
Consumer Finance ◽  
Credit Risk Management ◽  
Fusion Model ◽  
Gradual Improvement ◽  
Credit Reporting ◽  
Finance Industry ◽  
Depth Analysis

Traditional consumer finance is a modern financial service method that provides consumer loans to consumers of all classes. With the gradual improvement of China’s credit reporting system, big data credit reporting has effectively made up for the lack of traditional credit reporting and has been widely used in the consumer finance industry. In this context, the in-depth analysis of the specific application of big data credit reporting in the credit risk management of consumer finance and the strengthening of the research on the application of big data credit reporting in the credit risk management of consumer finance are urgently needed to be resolved in the economic and financial theoretical and practical circles’ problem. This article mainly studies the research on credit risk management of consumer finance by big data. The experimental results of this paper show that the model has a good forecasting ability, can distinguish between normal loan customers and default loan customers, and is suitable for practical personal credit risk control business. The prediction accuracy of the default model of the fusion model is 97.14%, and the default rate corresponding to the actual business is 2.86%. By combining the risk items such as the blacklist and gray list in the Internet finance industry, the bad debt rate and illegal usury can be well controlled to meet industry supervision.

Personal Credit Evaluation System Based on Decision Tree

2014 ◽  
Vol 644-650 ◽  
pp. 5840-5843
Author(s):  
Li Na Tan ◽  
Hai Long Wu
Keyword(s):  
Decision Tree ◽  
Rural Area ◽  
Evaluation System ◽  
Decision Tree Model ◽  
Current Account Balance ◽  
Tree Model ◽  
Credit Evaluation ◽  
Personal Credit ◽  
Wide Range ◽  
Credit Evaluation System

This paper analyzed personal credit evaluation system in rural area based on decision tree model. Firstly, it reviewed some references about credit evaluation methods and found that decision tree was a linear adaptive data-driven model with induction ability and a wide range of function approximation ability so that it could be applied into personal credit evaluation. Secondly, decision tree classified data samples consisting of two phases: constructing decision tree model and then classification stage. The first stage was to train data samples to establish a decision tree, and this process was divided into three steps which included feature selection, node splitting and tree pruning. The second stage was to put test samples into the established decision tree, and let it to classify from a new set of data. After that, it took advantage of the model to evaluate personal credit and selected the twenty indicators. The results showed that household assets, net assets and the existing current account balance were the most important three indicators for evaluating personal credit in rural area.

Internet Financial Credit Evaluation for the Small and Medium Enterprises

2014 ◽  
Vol 989-994 ◽  
pp. 5075-5077
Author(s):  
Yi Qing Lu
Keyword(s):  
Big Data ◽  
Credit Risk ◽  
Information Asymmetry ◽  
Financial Institutions ◽  
Evaluation System ◽  
Small And Medium Enterprises ◽  
Credit Evaluation ◽  
Financial Credit ◽  
Medium Enterprises ◽  
Credit Evaluation System

In this paper, a credit evaluation system based big-data is designed to change the information asymmetry between the finance institutions and enterprises, reduce the credit risk of internet financial institutions and investors, by utilizing the information and technology advantages. The research objective of this project have important theoretical and application value to the development of small and medium-sized enterprises (SME) credit evaluation system.

Retail Credit Risk Management in Indian Public Sector Banks

2012 ◽  
Vol 3 (8) ◽  
pp. 31-37
Author(s):  
Nayan J. Nayan J. ◽  
◽  
Dr. M. Kumaraswamy Dr. M. Kumaraswamy
Keyword(s):  
Risk Management ◽  
Public Sector ◽  
Credit Risk ◽  
Credit Risk Management ◽  
Public Sector Banks ◽  
Retail Credit

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.

An Investigation of Credit Risk Management Strategies of Private Commercial Banks of Bangladesh

2014 ◽  
Vol 2 (2) ◽  
pp. 77-87
Author(s):  
Abu Hanifa Md. Noman ◽  
Md. Amzad Hossain ◽  
Sajeda Pervin
Keyword(s):  
Risk Management ◽  
Credit Risk ◽  
Commercial Banks ◽  
Management Practices ◽  
Management Practice ◽  
Management Strategies ◽  
Third Party ◽  
Primary Data ◽  
Credit Risk Management ◽  
Risk Management Strategies

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.

Research on Credit Evaluation System of Electricity Retail Companies

2021 ◽  
Author(s):  
Zhiwei Ying ◽  
Tao Yu ◽  
Yupeng Huang ◽  
Hanfu Wang ◽  
Dunnan Liu ◽  
...  
Keyword(s):  
Evaluation System ◽  
Credit Evaluation ◽  
Credit Evaluation System
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