Research On Internet Financial Credit Risk Under The Impact Of COVID-19

In recent years,the economic situation at home and abroad has been complex and changeable,and the uncertain factors have increased significantly.The outbreak of COVID-19 in 2020 has had an unprecedented impact on people’s production and life.These factors have put forward higher requirements for the credit risk management of Internet finance,not only requiring the regulatory authorities to improve relevant mechanisms,laws and regulations,At the same time,it also puts forward higher requirements for the integrity and flexibility of the borrower qualification evaluation and credit evaluation system of financial institutions.This paper quantifies the impact of the epidemic on the borrower’s credit as the basis for evaluating the credit risk of the epidemic on Internet finance.Taking the loan data of Ren Ren loan platform from July 1,2019 to June 30,2020 as the research object,this paper analyzes the internal indicators and macroeconomic variables of the platform respectively.Due to the impact of the epidemic impact on the social fundamentals,according to the data characteristics of monthly repayment on the platform,this paper calculates the number of newly diagnosed people in COVID-19 every month within the statistical data range.Due to the excessive number of people,the logarithm of the newly diagnosed people in the borrower’s month is taken as the control variable to quantify the severity of the epidemic.Firstly,considering the impact of external shocks on the borrower’s credit,this paper selects the survival analysis model to include macroeconomic indicators into the index system.The survival analysis model can not only include time-varying variables such as macro data into the model,but also judge the impact degree of variables through the size of relative risk.Secondly,more detailed consideration is given to the impact of various indicators on borrowers under different quantiles under the impact of the epidemic.Due to the possible impact of various industries,the data are subdivided according to industries,and five industries are selected to carry out Bayesian quantile regression on their data before and after the epidemic.By considering the coefficient change degree of various indicators under different quantiles in different industries,a comparative analysis is carried out.Finally,through the analysis and regression of the data in 2019 and 2020 respectively,it is concluded that after the impact of the epidemic,the impact of macroeconomic indicators on the borrower’s credit is significant.At the same time,in the information of each borrower collected by the platform,the impact of many explanatory variables after the epidemic has decreased,but some explanatory variables such as annual interest rate,number of successful loans,age,gender,car loan and other factors,The impact of default risk on low-risk and high-risk borrowers has increased,but the degree of change and trend are slightly different for different industries.