Record Details

Research on Credit Risk Assessment of P2P Network Platform: Based on the Logistic Regression Model of Evidence Weight

Kasarinlan: Philippine Journal of Third World Studies

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Field Value
 
Title Research on Credit Risk Assessment of P2P Network Platform: Based on the Logistic Regression Model of Evidence Weight
 
Creator Yuan, Zhang
 
Subject —
Network Credit; Credit Risk Assessment; Logistic Regression; Weight of Evidence.
finance
 
Description As an emerging credit model, P2P network credit has been developing rapidly in recent years. At the same time, it also faces many credit risk problems. This paper focuses on the credit risk of borrowers, and constructs a model of WOE and logistic regression to evaluate the risk assessment of China’s P2P network platform, Hong ling Venture. The research results show that the main factors that affect the loan success rate of P2P lending platform include loan amount, annual interest rate, bidding transaction amount and proportion of repayment on time and so on. By constructing the model of combination of the logistic regression with weight of evidence, this paper provides an appropriate method to manipulate the borrowing information of loan borrowers and evaluates the borrowing behavior of borrowers simultaneously, so that P2P credit platform can reduce the credit risk caused by borrower.
 
Publisher Scitech Research Organisation
 
Contributor —
 
Date 2018-02-14
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
WOE; Logistic regression
 
Format application/pdf
 
Identifier http://scitecresearch.com/journals/index.php/jrbem/article/view/1415
 
Source Journal of Research in Business, Economics and Management; Vol 10, No 2: JRBEM; 1874-1881
 
Language eng
 
Relation http://scitecresearch.com/journals/index.php/jrbem/article/view/1415/1006
 
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Rights Copyright (c) 2018 Journal of Research in Business, Economics and Management