A Study On The Chinese P2P Borrower’s Credit Risk Assessment Based On The BP Neural Network Model

Peer to peer credit, P2P for short, which is a personal direct lending model based on the network platform. allows people to connect with one another to lend and borrow money online. Since it’s first introduced to China, our country is launching a great P2P network credit wave. At the end of Marsh2015, there have raised thousands of P2P credit companies in our country, achieving an online financing scale of50billion dollars. However, the geometric growth of the number of P2P network credit platforms does not represent the mature of the P2P network credit industry. P2P as a new credit model is still in the development process, and the industry is facing numerous problems. The companies in the industry are usually small in scale. And their risk management capability is far lower than traditional commercial banks. The most significant risk is the credit risk. However most P2P network platforms have not build their own credit assessment models yet.Firstly,the article analyzes the credit risk of theP2P borrowers from the perspective of credit. Secondly, the article introduces the basic principle and features of BP neural network and analyzes..the applicability of BP neural network model in credit risk assessment of P2P borrowers.Thirdly, on the basis of the theory and model of the traditional microfinance risk management, the article establishes P2P network credit risk assessment model based on the BP neural network, referring to the personal credit evaluation index system established by predecessors.At last,according to the borrowers’ personal information disclosed from P2Pnetwork platforms (Paipai Credit,365Easy Credit,etc),I select a number of indicators to be used in the P2P network credit risk assessment model based on the BP neural network for training and simulation. The training and simulation results show that the model has the capability of the assessment the borrowers’ credit risk, which means that the model is suitable for the P2P networks to assess the borrower’s credit risk.Finally, based on the research conclusions of BP neural network model as well as the internal and external environment of individual credit risk, this paper presents countermeasures and suggestions to promote the risk assessment system of P2P borrowers.