北京师范大学学报（自然科学版）2017，Vol.53Issue(1)：24-27,4.DOI:10.16360/j.cnki.jbnuns.2017.01.005
基于复杂网络和机器学习的P2P用户违约预测
Predicting bad P2P loans with machine learning and complex network algorithm
林国强 1赵毅鸣 1况青作 1樊瑛1
作者信息
- 1. 北京师范大学系统科学学院,100875,北京
- 折叠
摘要
Abstract
From 2013,the P2P (peer-to-peer) companies render people easy access to small loans.P2P has become an important part and trend of internet finance industry.Although companies benefit from loan interest,bad loans can be fatal for their future.Hence prediction of bad loans can help those companies avoid loss and thrive.Here we analyze mobile phone contacts from clients of Wecash,a prominent internet finance company.We build a directed network capturing relationship of each client.We then apply a model with machine learning to predict probability of a client failing to repay the loan.Interestingly,network structure and client neighborhood can shed some light on client credit.关键词
复杂网络/互联网金融/P2P/机器学习Key words
complex networks/internet finance/peer-to-peer/machine learning分类
管理科学引用本文复制引用
林国强,赵毅鸣,况青作,樊瑛..基于复杂网络和机器学习的P2P用户违约预测[J].北京师范大学学报（自然科学版）,2017,53(1):24-27,4.
