网络与信息安全学报2017，Vol.3Issue(12)：1-7,7.DOI:10.11959/j.issn.2096-109x.2017.00222
基于神经网络模型的网络借贷高危企业信用风险的识别研究
Credit risk identification of high-risk online lending enterprises based on neural network model
摘要
Abstract
The rapid development of online lending alleviates the difficulty of financing for small and micro enterprises to a certain extent, but it also exposes the credit risk identification problem of online lending platform. In order to fully identify the characteristics of high-risk network lending enterprises, small and medium-sized network lending companies were selected as samples, and indicators that were highly correlated with risk identification were chosen as indicators variables. And by using the BP neural network algorithm model, the credit risk identification rate and credit risk classification accuracy rate of high risk network lending enterprises, under different conditions, were obtained. The results show that the credit risks of high-risk network lending enterprises are highly recognized, and have the characteristics of high recall rate and high accuracy.关键词
高危网贷企业风险识别/指标筛选/神经网络/召回率Key words
high risk online lending enterprise risk identification/index screening/neural network/recall rate分类
管理科学引用本文复制引用
王茂光,朱子君..基于神经网络模型的网络借贷高危企业信用风险的识别研究[J].网络与信息安全学报,2017,3(12):1-7,7.基金项目
网金中心合作基金资助项目(No.020676116004) （No.020676116004）
北京大学合作基金资助项目(No.020676114004) （No.020676114004）
Cooperation Project with Network Finance Center (No.020676116004), Cooperation Project with Peking University (No.020676114004) （No.020676116004）
