我国P2P网络借贷信用风险影响因素研究——基于排序选择模型的实证分析
On the Influence Factors of Credit Risk of Online P2P Lending in China:Based on an Empirical Analysis by the Ranking Selection Model

P2P（peer-to-peer）网络借贷是一种借助网络平台，由个人与个人间互为借贷双方的小额借贷交易。它作为互联网与民间借贷相结合的新兴金融模式，具有较高的信用风险。采用排序选择模型，基于excelVBA数据挖掘技术截取多个P2P网站数据，对平台信用风险的影响因素进行实证分析，结果表明：个人特征、信用变量、历史表现、借款信息分别对网络借贷信用风险存在正向影响，由此发现网站提供的信息对投资者避免信用风险没有起到实质作用。
Online P2P (peer-to-peer) lending, is microfinance transactions by people lending to each other, with the aid of online platforms of electronic business. As a new financial model of folk loan business conducted with the Internet technology, it has a higher credit risk. This paper uses the ranking selection model to analyze the influencing factors of the credit risk of online lending based on data from some P2P sites extracted by excel VBA Data Mining, and the results showed that: personal characteristics, credit variables, historical performance, loan information each had a marked positive influence on the credit risk of online lending. We found that the information provided by websites for investors to avoid credit risk did not play a substantive role.