Research On Network Loan Credit Risk Measurement Under Asymmetric Information

With the development of information technology and financial engineering,online lending has gradually become an extremely important form of financial transaction.Due to the asymmetry of information between the two parties,credit risk is a very important risk in the online loan industry.Therefore,the measurement of credit risk it is one of the core contents of online loan risk assessment,and it is also a hot topic in Internet finance research.This paper studies the measurement of online credit risk under asymmetric information.The main research contents are as follows:(1)Based on the factor analysis method and Logistic regression model,the default probability model of loan credit risk is established,and the test data of “UMS” platform is used for empirical analysis.The online loan credit default probability model is a good illustration of the probability that the borrower’s relevant information has a default on online loans,which has certain practicability.(2)Constructing an asymmetric information measurement model,and using this model to measure the degree of asymmetric information in the online loan market interest rate and the Shanghai interbank loan rate.The results show that: in the case of low market interest rates,asymmetric information the degree of symmetry is relatively large.(3)Based on the information asymmetric measurement model,construct the residual regression model of successful loan application and the residual regression model of successful repayment times;then apply the above two models to the test data of “UMS”.the empirical analysis is carried out.By detecting the relationship between the number of successful repayments of borrowers in different periods and the number of loan applications and asymmetric information,asymmetric information has a significant impact on the credit risk of online loans.