Study On Credit System Of P2P Network Credit Platform Based On Its Characteristic

P2P network credit rapidly spreading all over the major internet country as one of the most representative and innovative business models of web banks.P2P network credit stand for "peer to peer lending",means that those who get personal investment idea lend the fund to those who need it through the third party network platform. The file of warning of network credit risk published by China CBRC abbreviated it as "Lend for everyone".According to the statistics made by "The home of network credit", there are121large-scale platform of network credit as of1st September,2014,the volume up to20billion per month. The quantity of platforms doubled than61which came from the beginning of2013. It is foreseeable that in China, the quantity and volume will keep a rapid growth in pace of the social awareness of P2P.However, the credit mechanism is not perfect in China. People’s awareness of credit is also inadequate. The hidden risks became bigger as the platforms of network credit developing rapidly. Also, the ability of risk-controlling is unsynchronized, which causes the collapse of a big amount of platforms of network credit. It is obviously that the risk of credit is the biggest one that faced by network credit corporations in China, the management and control of the credit risk play a vital role. But the management technology of p2p network credit risks is falling behind, especially the personal credit scoring, which is core issue of the management of credit risks, simply imitate the traditional system, cannot meet the need of the security of the funds from the both parties to the transaction, not to mention the requirements of timeliness. As such, it is necessary to know how to build a scientific and effective evaluation system and to improve the management level of credit risks.The thesis focus on how to build a scientific and effective evaluation system of the personal credit scoring, optimize the traditional assessment factors of system of the personal credit scoring, optimize the weights of different factors, and score based on the internet big data to get the evaluation reports of personal credit. Strive to ensure objective, fair comprehensive while focus on the efficiency. To make a remarkable contribution to the study of personal credit evaluation system of P2P network credit platform.