Multidimensional research on credit risk of P2P network credit based on big data

Abstract

The most research of the P2P network loan and lending industry mainly focused on the risk with qualitative analysis and factors method. However, the problems and the measures would be diverse in different regions and P2P network credit platform environment. There were 1357 P2P network credit platform which was more active in china; the trading volume of P2P network loan and lending reached 147 billion Yuan, which had already been the largest P2P loan and lending trading market in the world. Selected the Guangdong P2P network loan and lending company in China as the research object, through detailed data investigation on the credit risk of Guangdong P2P company in china, analyzed the background, current situation and existing problems of Guangdong P2P network loan and lending company, carried out the modeling and analysis on the basis of the theory of asymmetric information, big data and the information economics theory of data mining analysis. The supervision system model of P2P network credit had been established from risk prevention perspective, and its implement shown that the risk supervision system model of P2P network credit had reference value for the risk management of regional P2P platform.