Leveraging Federated Learning for Unsecured Loan Risk Assessment on Decentralized Finance Lending Platforms

Qian'ang Mao, Sheng Wan, Daning Hu, Jiaqi Yan, Jin Hu, Xuan Yang

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

2 Citations (Scopus)

Abstract

This study proposes a novel privacy-preserving unsecured loan risk assessment system that allows decentralized finance (DeFi) lending platforms to offer loans without collateral. This system leverages federated learning methods to train risk assessment models using both off-chain and on-chain data sources, to more accurately evaluate borrower default risk for unsecured loans. Moreover, this system is built on a trusted execution environment (TEE) with program-level isolation, which provides a secure and efficient solution for DeFi platforms to offer unsecured loans. The effectiveness of this platform is validated through a set of simulation experiments. These experiments underscore the capability of the federated learning models to accurately assess borrower default risk while preserving stringent data privacy standards. The unique and innovative system design we proposed offers significant advancements for DeFi lending platforms. These improvements have the potential to greatly enhance DeFi platforms' inclusiveness by offering unsecured loans while maintaining efficiency, and security.

Original languageEnglish
Title of host publicationProceedings - 23rd IEEE International Conference on Data Mining Workshops, ICDMW 2023
EditorsJihe Wang, Yi He, Thang N. Dinh, Christan Grant, Meikang Qiu, Witold Pedrycz
Pages663-670
Number of pages8
ISBN (Electronic)9798350381641
DOIs
Publication statusPublished - 2023
Externally publishedYes
Event23rd IEEE International Conference on Data Mining Workshops, ICDMW 2023 - Shanghai, China
Duration: 1 Dec 20234 Dec 2023

Publication series

NameIEEE International Conference on Data Mining Workshops, ICDMW
ISSN (Print)2375-9232
ISSN (Electronic)2375-9259

Conference

Conference23rd IEEE International Conference on Data Mining Workshops, ICDMW 2023
Country/TerritoryChina
CityShanghai
Period1/12/234/12/23

Keywords

  • blockchain
  • credit scoring
  • federated learning
  • unsecured lending

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