P2P lending platform risk observing method based on short-time multi-source regression algorithm

Pan Liu, Huakang Li, Guozi Sun*

*Corresponding author for this work

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

3 Citations (Scopus)

Abstract

Peer-to-Peer (P2P) lending is a popular way of lending in contemporary Internet financial filed. Comparing with the traditional bank lending, the annual risk evaluation is no longer applicable for P2P platform because of the short life cycle and a lot of transaction records. This paper presents a method to dynamically evaluate the operation risk of P2P plat- forms based on a short-time multi-source regression algorithm. Dynamic time windows are used to split up the lending records and linear regression method is used to quantify the dynamic risk index of P2P platforms. The experimental results show that the proposed method can reflect the visible operation situation of platforms, and give investors dynamic risk assessment and effective tips of the platforms.

Original languageEnglish
Title of host publication2018 IEEE International Conference on Communications, ICC 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781538631805
DOIs
Publication statusPublished - 27 Jul 2018
Externally publishedYes
Event2018 IEEE International Conference on Communications, ICC 2018 - Kansas City, United States
Duration: 20 May 201824 May 2018

Publication series

NameIEEE International Conference on Communications
Volume2018-May
ISSN (Print)1550-3607

Conference

Conference2018 IEEE International Conference on Communications, ICC 2018
Country/TerritoryUnited States
CityKansas City
Period20/05/1824/05/18

Keywords

  • Credit assessment
  • Operation risk
  • P2P lending
  • Time window segmentation

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