Research And Development Of P2P Network Loan Credit Risk Assessment System

As the main representative of Internet finance in our country,peer-to-peer lending develops rapidly in our country with the advantages of low investment threshold,convenient and flexible transaction.It is developing rapidly in our country.However,at a very early stage,due to the low access threshold of the platform,a large number of platforms were brought online in a short period of time.There are good and bad ones in these platforms.Up to now,more than 2,000 platforms have made cash withdrawal difficulties,closed down and even escaped.The platform for this phenomenon occupies more than half of the market.China's commercial banks and financial markets are in the transitional and emerging stages of development,lack of in-depth study of the basic theory of personal credit risk assessment,and the development of personal credit information system lags behind and slow.Therefore,it is of great practical significance to study the credit risk of P2 P network lending.Using the knowledge of system development,this paper studies and designs the credit risk assessment system of P2 P network lending platform by combining with the network robotics,machine learning and modeling algorithms.The system mainly includes six major functions,including default function of borrower,credit rating function of net loan platform,function of publishing internet financial information,ranking function of net loan,and forum function.Borrower's default forecasting function and the credit rating function of the online loan platform are the focuses of this paper.This paper begins with the development status of P2 P lending platform at home and abroad,as well as the operation mode of P2 P lending platform in our country at present.It analyzes and studies the formation mechanism of credit risk of P2 P lending platform from three aspects: borrower,investor and industry itself.Then,according to the credit risk formation mechanism and its influencing factors of the borrowers in P2 P network loan,referring to the previous research on the credit risk assessment index system of borrowers and the personal information that needs to be provided in the loan platform of the network loan,12 evaluation indexes are finally established and established Borrower Credit Risk Assessment Index System.Use the Python language to obtain 899 complete borrowing data from the Peer-to-Peer lending Website as a training sample.On the spark platform,we train the data by calling the random forest algorithm,and finally get the default forecasting model of the borrower.Then,using the combination of qualitative index and quantitative index,this paper established the credit rating index system of P2 P online loan platform,and according to the classification of credit rating of CCXI,combined with the development status of P2 P network credit platform,determines the credit rating level of online loan platform,Support vector machine technology training network credit platform credit rating model.The system conducts a credit risk assessment for P2 P network lending platform and borrowers,which can attract more network borrowers to use the platform for platform managers to make profits.On the one hand,lenders can not only recover loans on time but also obtain the highest possible Interest rates.On the other hand,it will ensure that borrowers can get proper loans on time and in full amount,thus safeguarding the interests of the three parties and making P2 P network lending platform embark on a path of sound development.