A predictive indicator using lender composition for loan evaluation in P2P lending

Yanhong Guo (), Shuai Jiang, Wenjun Zhou, Chunyu Luo and Hui Xiong
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Yanhong Guo: Dalian University of Technology
Shuai Jiang: Dalian University of Technology
Wenjun Zhou: University of Tennessee
Chunyu Luo: Dalian University of Technology
Hui Xiong: Rutgers University

Financial Innovation, 2021, vol. 7, issue 1, 1-24

Abstract: Abstract Most loan evaluation methods in peer-to-peer (P2P) lending mainly exploit the borrowers’ credit information. However, the present study presents the maturity-based lender composition score, which exploits the investment capability of a group of lenders who fund the same loan, to enhance the P2P loan evaluation. More specifically, we extract lenders’ profiles in terms of performance, risk, and experience by quantifying their investment history and develop our loan evaluation indicator by aggregating the profiles of lenders in the composition. To measure the ability of a lender for continuous improvement in P2P investment, we introduce lender maturity to capture this evolvement and incorporate it into the aggregation process. Our empirical study demonstrates that the maturity-based lender composition score can serve as an effective indicator for identifying loan quality and be included in other commonly used loan evaluation models for accuracy improvement.

Keywords: P2P lending; Maturity assessment; Lender composition; Loan evaluation (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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DOI: 10.1186/s40854-021-00261-1

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