Value Optimization Method Of Network Lending Platform Based On WoE-Logistic Credit Scoring Card Default Prediction Model

P2P online lending is a new lending model that combines the characteristics of Internet technology and small loan.It develops rapidly in China with the advantages of low threshold,wide coverage and convenient transaction process.However in the platform number and size of booming growth at the same time,the borrower default and bankrupt incident also occurred frequently,which not only for the general investors caused great losses,at the same time also damaged the P2P network industry reputation,a blow to investor confidence,the healthy and standardizing development has become a P2P network industry loan a stumbling block on the road.Information asymmetry is a major cause of lead to this phenomenon,in order to alleviate the damage caused by asymmetric information,many network platform set up his own credit assessment system,however,due to the credit industry is an emerging industry,the domestic research on the credit risk is not perfect enough,so the net credit platform for default risk prediction ability is uneven,as a whole is relatively low.In view of the above situation,it is very necessary to find a more scientific,effective and unified credit evaluation method,which can help the online loan platform and investors to more accurately identify the risk of default rate before the loan,so as to improve the total value of the loan of the online loan platform and promote the healthy development of the online loan platform.Credit score card model is a mature default prediction method in foreign countries,especially in the field of credit risk assessment and financial risk control has been more widely used,this model has the advantages of simple,intuitive,convenient,etc.,has a good application prospect in the field of network lending.In China,the credit score card model is mainly applied to the default risk prediction of online loan platforms such as"renrendai”and"paipaidai".However,from the perspective of historical data,the default prediction accuracy of the credit score card model used by these platforms is not high,which will lead to the low or even negative total value of the loan business of online loan platforms.In this paper,WoE-Logistic credit score card model is studied to see whether WoE-Logistic credit score card model can improve the total value of loans for online loan platforms by improving the prediction accuracy of default risk by combing related literatures and taking a well-known online loan platform as the research object based on the existing conclusions of related literatures.The empirical research results show that WoE-Logistic credit score card model can be applied to the online loan platform to evaluate the pre-loan default risk,which can increase the total value of loan.Moreover,after certain improvement of WoE-Logistic credit score card model in this paper,the increase of total value of loan can be more significant.It means that WoE-Logistic credit score card model has a very good application prospect in the field of P2P online loan default risk prediction.It can help the online loan platform to more correctly identify the default risk of loan applicants and optimize the loan business value of the online loan platform,thereby promoting the healthy development of P2P online loan industry.