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A Data-Analytics Approach for Risk Evaluation in Peer-to-Peer Lending Platforms
- Source :
- IEEE Intelligent Systems. 35:85-95
- Publication Year :
- 2020
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2020.
-
Abstract
- The goal of this article is to investigate the roles of individual behavior characteristics and Internet finance industry risk in the light of bank run theory for P2P. We know that risk evaluation is clearly important for peer-to-peer (P2P) lending platforms in China, as during the last two years, the industry has experienced thousands of platform crashes. Traditional approaches to evaluate enterprise risk are increasingly ineffective in this industry, due to the difficulty of assessing the real information. In addition, the Internet business model makes it possible to record new kinds of information. By applying a data-driven analytics method, we build an intelligent risk evaluation model for P2P platforms that have comparable targeting platforms. The case study shows that our risk evaluation method can generate early warning signals regarding platform or industry risk, which is able to provide effective supporting for P2P business in practice.
- Subjects :
- Warning system
Computer Networks and Communications
business.industry
Computer science
Bank run
02 engineering and technology
Peer-to-peer
Business model
computer.software_genre
Data science
Enterprise risk management
Artificial Intelligence
Analytics
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
The Internet
business
computer
Financial services
Subjects
Details
- ISSN :
- 19411294 and 15411672
- Volume :
- 35
- Database :
- OpenAIRE
- Journal :
- IEEE Intelligent Systems
- Accession number :
- edsair.doi...........a529278c71f2b1180aac7bf921fb922d