Research On Credit Risk Assessment Of Borrowers In P2P Network Lending

As a new type of Internet Finance mode,P2 P Internet lending provides new financing channels for capital demanders through the internet.It is a new type of lending mode,which can complement traditional finance.For the small and micro enterprises and the masses,which are not paid enough attention to by traditional finance,P2 P network lending can provide better services for them.However,the P2 P online lending industry started late in China,and its development is not mature.The current situation of "no threshold,no industry standards,no regulatory body" in the P2 P online lending industry makes the platform face many risks.In recent years,the phenomenon of platform closure and runaway happens frequently.The risk control and management of the P2 P online lending platform need to be solved urgently.Among many risks,the borrower's credit risk is one of the main risks faced by the online lending industry.This paper takes the borrower's credit risk as the breakthrough point to carry out empirical analysis and analyze the impact of borrower's information on credit risk.This paper first introduces the related concepts of P2 P online lending,and analyzes the risks faced by P2 P online lending and the relevant theoretical basis of P2 P online lending.Before the empirical analysis,the credit risk evaluation index system of the borrower was established.The construction of the system refers to the way that several traditional commercial banks in China evaluate personal credit and the index system built in relevant domestic literature,and combines the relevant information of the borrowing target on the selected platform “everyone's loan” to construct a set of applicable information.Credit risk evaluation index system for borrowers on the online loan platform.Subsequently,the study was conducted using 61,186 valid transaction data from January to December 2015,which was crawled from the “Everyone Loans” platform.In the empirical research,the whole descriptive statistical analysis of all the data is carried out first,followed by a detaileddescriptive analysis of the transaction data of the default;the multi-collinearity between the variables is analyzed before the variables are included in the model for regression.After confirming that the variables were interconnected independently,the samples were empirically analyzed using a binary logistic regression model.The results show that the seven indicators of the borrower's age,education,income,borrowing rate,borrowing period,borrower's credit rating and borrowing overdue have a significant impact on the borrower's credit risk,including age,borrowing rate,borrowing period,and overdue loan.The number of times has a significant positive correlation with the default rate of the borrower;the borrower's education,income,and credit rating have a significant negative correlation.Finally,based on the research conclusions and the current situation of China's P2 P online lending,the author puts forward suggestions from the perspectives of investors and online lending platforms.This paper hopes that the research results and risk assessment models can provide reference value for investors and platforms to correctly identify,prevent and resolve credit risks.