摘要
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 lend-ing 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 infor-mation provided by websites for investors to avoid credit risk did not play a substantive role.
出处
《财经理论与实践》
CSSCI
北大核心
2015年第1期2-6,共5页
The Theory and Practice of Finance and Economics
基金
湖南省哲学社会科学基金项目(12YBA071)