Analysis On The Influencing Factors Of Borrower's Default Behavior In P2P Network Borrowing

With the rapid development of intermet finance,China's P2P network loan industry has also developed explosively.Compared with traditional financial institutions,the P2P network loan model not only provides simpler and faster borrowing methods for individual users and small and micro enterprises,but also meets China's policy direction for supporting inclusive financial development.As a typical representative of internet finance,P2P network lending has played a very importBnt role in promoting the economic goals of financial services entities,as well as the development of the financial industry.In the background of China's P2P network loans,"no entry barriers,no industry standards,no regulatory institutions,,a large number of investors lacking financial expertise flocked in,and the P2P network loan industry accumulated in the process of continuous development.A series of risks and problems have been exposed,and the online loan platform has been frequently ran off and stopped due to poor management.Ii recent years,in order to regulate the development of the P2P industry,China has successively issued a series of regulatory policies.The risk originated from the platform itself has been effectively controlled,but the P2P industry's borrowers have more serious breach of contract,both for investors and for platforms.Caused a huge loss.It can be seen that in order to improve the competitiveness of the online loan platform and ensure a virtuous circle of development of the P2P industry,it is necessary to control and prevent P2P borrowers from defaulting.Therefore,this article will conduct an empirical study on the factors that influence borrowers' default behaviors in P2P network borrowing and establish a prediction model for borrower default behavior.This will not only help investors make correct investment decisions,but aiso help P2P platform operators to Borrower's breach of contract conducts effective response and control.This article first sorts out relevant theories and literatures to provide the theoretical basis for the following analysis.Secondly,this article analyzes the default of the borrower in the current stage of P2P network loan based on the data disclosed by the online mutual-credit platforms in the China Mutual Gold Association and the cases of default by some platform borrowers.Then,this paper uses logistic regression model to study the influencing factors of P2P network borrower default behavior,and pays attention to the impact of borrowing interest rate and credit rating on borrower default behavior.At the same time,in order to better understand the borrower's bonrowing beha'vior,this paper constructs a prediction model for borrower default behavior.In the test of model prediction effect this paper first uses the classifieation table to test,but considering that the classification table has unsuitability and unbalance Due to the lack of datasets and fixed thresholds,the prediction of the model using the classification table is not accurate enough.The ROC curve can make up for the defects of the classification table well.Therefore,this article uses the ROC curve to retest the model prediction effect,making the conclusion of the article more convincing.The main conclusions of this paper are as follows:First,compared with traditional financial institutions,the borrower default in the P2P online loan industry is more serious,and most platforms have the behavior of‘‘whitewashing,the overdue rate.The disclosed industry risk is lower than the actual value.Second,the borrowing rate is an important factor that causes the borrower to default,and the borrower who promises a higher borrowing rate will bear the greater financial pressure and the possibility of default.Third,the credit rating system of the platform is effective,and the assessed credit rating can,to a certain extent,alleviate the problem of information asymmetry in online loan transactions.Investors can also evade the issue of breach of contract based on the credit rating.Fourth,the predictive model of default behavior of borrowers constructed in this paper has good prediction effect and has a high reference value.This article believes that the P2P online loan platform must not only conduct a rigorous review of the authenticity of the borrower,s information before lending,ensure the aocuracy of the credit rating results,and strictly control the issuance of high interest rate borrowing targets.It is also necessary to predict the borrower's breach of contract to determine the likelihood of the borrower defaulting on the loan.The combination of the two can effectively alleviate the borrower's breach of contract on the P2P online loan platform and promote the healthy and sustainable development of the platform.