CF-NN: a novel decision support model for borrower identification on the peer-to-peer lending platform. Issue 22 (17th November 2021)

• Record Type: Journal Article
• Authors: Pan, Yuchen; Chen, Shuzhen; Wu, Desheng; Dolgui, Alexandre
• Is Part Of: International journal of production research. Volume 59:Issue 22(2021)
• Page Start: 6963
• Page End: 6974
• Publication Date: 2021-11-17
• Subjects: Peer-to-peer lending platform -- default risk -- bad borrowers -- neural network -- collaborative filtering; Factory management -- Periodicals; 658.57
• DOI: 10.1080/00207543.2020.1832270
• Languages: English
• ISSNs: 0020-7543

Abstract

Abstract : With the prevalence of online individual micro-loans, an increasing number of peer-to-peer lending platforms have been established during the last ten years. One main problem for these platforms is to accurately identify the 'bad' applicants with high default risk. In this paper, we propose a CF-NN model that combines neural network and collaborative filtering for identifying high-risk borrowers. It is demonstrated in the experimental analysis that the CF-NN model significantly outperforms other widely used data mining models on the identification of bad borrowers. Moreover, the experimental results show that, to achieve the best performance in borrower identification, the CF-NN model should be equipped with parameters of intermediate values.