Borrower Credit Risk Assessment Of The Lending Platform Based On P2P Network Applied Research

P2P network lending is a new type of private lending,its appear and development makes private lending more sunlight and diversification,allocation of social idle funds more rational, increased investment channels for Chinese residents,in making up for the deficiency of traditional finance,it also promotes the development of China’s financial system. But at the same time,we must also recognize that P2 P lending network in China is still a new thing,P2 P network lending platform has the property of financial institutions,but no financial license,completely free in the regulation.The high demands of the market and lack of industry threshold,were barbaric by P2 P network lending platform.Due to the lack of China’s credit system,the borrower’s moral hazard is inevitable,once the economy suffered a cold,P2 P network lending capital chain is likely to fracture.At present,a lot of P2 P network lending platform is facing more and more risk.The biggest risk is the credit risk.At present there are few lending to P2 P network platform to build their own credit risk assessment model.In this paper,it first introduce and study the concept,characteristics and development of network lending,explore the main factors that affect the credit of the borrower in the network,according to pat,Liu jin suo,Yin xin loan borrower’s disclosure of personal information network platform,from the perspective of credit,analysis of P2 P networks borrowing the credit risk of borrowers in this role,reference to our country commercial bank personal credit and foreign lending to P2 P network platform of borrower credit index system to select several indicators,Then based on the BP neural network、Improved BP neural network and Logistic model for P2 P network loan borrower credit risk for training and simulation. In this paper, according to the BP neural network model、Improved BP neural network and Logistic model to analyze the research results found that the BP neural network model can better evaluate P2 P lending in the borrower’s credit risk. According to the conclusion and to meet the requirements of personal credit risk assessment, First, we construct the credit risk evaluation index system of P2 P network lending platform. Secondly, select the appropriate credit risk assessment model, Finally, based on the index system and evaluation model of the borrower’s credit rating is given. in this paper, the BP neural network model is proposed to evaluate the credit risk of the borrower in the P2 P network. At the same time, this paper suggests that the comprehensive strength of the P2 P platform should promote industry data sharing, At present, the data are independent of the P2 P network lending platform, The borrower’s credit situation has not been carried out and communication, A waste of data resources, on the other hand, convenient for fraud in different platform of resort to deceit, At the same time, they have a relatively low cost of crime, and sometimes may trigger a chain reaction, and then cause a number of problems. So the data sharing can improve the security of the platform, and can strengthen the cooperation between platforms, and improve the credit system of our country. This can make our country P2 P network lending platform can be safe, stable and healthy development.Finally, the establishment of a unified, scientific personal credit risk rating system, Establish a database on credit, Can objectively evaluate the personal credit, Increase personal default cost, So as to establish a good market economy environment. Ultimately through the government, banks, P2 P Platform Co and the joint efforts of individuals, The problem of improving the credit risk assessment of the borrower in the P2 P network lending platform, This paper also puts forward the countermeasures and suggestions of improving the credit risk assessment system of the credit risk in the P2 P network. Therefore, this study has some theoretical value and practical significance.