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The Borrowers’ Credit Evaluation Research Of Peer-To-Peer Lending In Domestic

Posted on:2017-03-30Degree:MasterType:Thesis
Country:ChinaCandidate:S J QiuFull Text:PDF
GTID:2359330488951442Subject:Applied Statistics
Abstract/Summary:PDF Full Text Request
In foreign countries,the starting time of the Peer-to-Peer Lending just two years earlier than the domestic.But their Peer-to-Peer Lending development is more healthy and orderly than our country.On the one hand the foreign legal and regulatory is more mature,on the other hand long tim e ago the foreign governments pay attention to the personal credit investigation.Cred it risk is the root cause of default.So this article focuses on research on personal credit.Rely on the studies of the borrower charac teristics this ar ticle constructs the credit evaluation model of Peer-to-Peer Lending,which is used to red uce the credit risk of loan.The Peer-to-Peer Lending is a typical "Internet +" projects,it has the features of the Internet,but its essence still is lending activities.Therefore,this article refer to the assessm ent model of traditional lending in domestic and ab road,include China construction bank and the FIC O.Through the comparative and analysis of two model combining with the characteristics of Internet the article selected evalu ation indexes at the sam e time to for m a new credit evaluation system of Peer-to-Peer Lending.In this paper,the data source is “renrendai”.Afte r preprocessing and grouping,the data is divided into two groups,a group containing 1200 samples as the experimental group and another group containing 300 samples as the test group.In the process of evaluate clas sification variables,this article transform the variables with weight of evidence.This article builds up a new assess ment model with log istic regression.Through the inspection,we found th e new assessment model can be used to assess the borrower credit.Finally,the article summarizes and forecasts the future of Peer-to-Peer Lending in our country.
Keywords/Search Tags:Peer-to-Peer Lending, CreditEvaluation, logistic regression
PDF Full Text Request
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