Research On Credit Evaluation Of P2P Loan Loan

P2P(peer to peer) net loan is a new loan model that individuals lend to each other through the network platform under the background of the rapid development of the Internet. Borrowers publish the demand of the loan on P2 P network platform. Investors lend funds to the borrowers through the platform to complete the transaction. It shares all the chips, third-party payment, O2O(online to offline)together to create the financial 2.0 era of the Internet. Since then, P2 P agencies in China set off a wave of popularity. By the end of 2013, nearly 40 network credit platform have been included everybody loan, security credit, Yi Xin loan, Hong Ling venture capital and so on.The development of this trend is beyond the anticipate of many people. The unsecured and the highest amount of hundreds of thousands for personal service mode, provides business services that banking, the trust and small loan companies are unable to provide. They meet the needs of special people, solve the difficulties of loan and financing for many individuals and micro enterprises. They can also help investors get a better income, and still showed a huge market potential up to now. But at the same time of meeting the demand, this kind of folk credit business takes more risks and produces more problems than commercial banks.In the business processes of P2 P net loan, the evaluation of credit for borrowers is the foundation and an important part of the overall credit rating of net loan project. So this paper is mainly to evaluate the credit in the borrower’s loan. In the comprehensive study of the method of personal credit evaluation and combining with the characteristics of P2 P network loan, this paper plans to establish the corresponding evaluation system of borrower’s credit under the basis of the established index system at home and abroad. According to the index system, it will establish a model of corresponding BP neural network. And then it will get the optimization model through the genetic algorithm to optimize the model of BP neural network. By using the model, we can meet the needs of different network borrowers for credit evaluation. For P2 P network platform about loan, it has played an important role as a reference for improvement and optimization of credit evaluation methods. In some certain sense, it can promote the healthy development of platforms of P2 P credit.In this paper, the data of five domestic representative P2 P net loan platforms are used to validate the validity and usefulness of the model. The result shows that the BP neural network model has better convergence optimization and predictive capabilities and the output is more accurate after optimization. The model can be used to evaluate the borrower’s credit better, so that the operational risk of P2 P net loan platform has a better control.