Research On The Determinants Of Borrowers' Default Risk In Online P2P Lending

As a pioneer of Internet finance,P2P online lending has been rapidly expanding in China since 2012.However,due to the immature market,related issues have gradually emerged,and risk control and evaluation have become the core of the current development of P2P online lending.In this paper,according to the characteristics of credit risk of P2P loan borrowers,loan default rate is the dependent variable,two methods of binary logistic regression and decision tree are used to construct the borrower's credit risk assessment model,and the key factors affecting the default of the borrower are selected to reduce the platform.The probability of default risk.P2P lending is an emerging product of financial lending under the catalysis of the Internet.It has obvious characteristics of the Internet.The core of its operation is the risk assessment of the borrower's personal credit.This article first uses literature analysis methods to conduct in-depth research on P2P lending related theories,personal credit assessment model,credit risk,and Logistic regression from 2007 to 2017.Then,the data mining method is used to capture the "credit of everyone"."The platform borrower's real information data,establishment of binary logistic regression model and decision tree model to conduct empirical research on the influencing factors of the borrower's default behavior,research found that the credit rating is still the main reference for investors to choose high-quality borrowers.In addition,the level of interest rates on borrowing,the borrower's income,and the state of the assets(whether or not they own property)are also important elements that investors need to focus on.In addition,investors need to carefully consider the borrower's academic status,do not be fooled by the borrower's high degree of education,there may be academic fraud,high academic qualifications and low credit and high IQ crimes.Finally,on the basis of theoretical and empirical research,relevant countermeasures and suggestions are proposed to improve the credit risk assessment and prevention system for borrowers,from expanding data sources,strengthening regulatory review,sharing data sharing,strengthening investor risk education,and establishing professional credit ratings.The five perspectives of the organization are elaborated separately.