Research On Individual Credit Evaluation System Of P2P Lending Platform Based On Analytic Hierarchy Process

As a frontrunner in Internet finance emerging in China since 2007,peer to peer lending(P2PL),the micro and small lending model,with its advantages of high yield,low entry barriers and easy operation,has rapidly gained popularity.By April 30 th,2016,there are 4,029 P2 P lending platform in operation in China,with a growth rate of over 4 percent.However,low entry barriers of the non-standardized industry lead to the frequency of scandals.The industry,for instance,was recently startled by Ezubo or Ezubao's being suspected of running illegal business.The one of reason is borrower's overdue payments,leading to run on the P2 P lending platform,ultimately resulting in capital chain rupture.And with the central bank officially approved eight institutions personal credit investigation business,we believe that the history of personal credit will also be fully reflected in the Internet.Therefore,the purpose of the thesis is,taking the existing law loopholes and incompetent supervision and administration into consideration,to find out a way to manage and control the risks of P2 P platform when market is properly regulated and law improved.Starting from how to build an effective individual credit evaluation system,the thesis,by optimizing the evaluation factors in traditional individual credit evaluation model and adding new weights with the help of AHP,discusses the building of an individual credit evaluation model on the basis of Internet big data scoring,which can screen and select loaner with good credit effectively and conveniently and ensure the review process objective,fair and comprehensive.