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

Yanhong Guo; Shuai Jiang; Wenjun Zhou; Chunyu Luo; Hui Xiong

doi:10.1186/s40854-021-00261-1

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

Yanhong Guo, Shuai Jiang, Wenjun Zhou, Chunyu Luo, Hui Xiong

Rutgers Business School, Management & Information Systems

Research output: Contribution to journal › Article › peer-review

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.

Original language	English (US)
Article number	49
Journal	Financial Innovation
Volume	7
Issue number	1
DOIs	https://doi.org/10.1186/s40854-021-00261-1
State	Published - Dec 2021

All Science Journal Classification (ASJC) codes

Finance
Management of Technology and Innovation

Keywords

Lender composition
Loan evaluation
Maturity assessment
P2P lending

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10.1186/s40854-021-00261-1

Cite this

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title = "A predictive indicator using lender composition for loan evaluation in P2P lending",

abstract = "Most loan evaluation methods in peer-to-peer (P2P) lending mainly exploit the borrowers{\textquoteright} 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{\textquoteright} 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 = "Lender composition, Loan evaluation, Maturity assessment, P2P lending",

author = "Yanhong Guo and Shuai Jiang and Wenjun Zhou and Chunyu Luo and Hui Xiong",

note = "Funding Information: This research was partially supported by the Natural Science Foundation of China (Nos. 71974031, 71771034), the Chinese Universities Scientific Fund (No. DUT19RW216) and the Economic and Social Development Project of Liaoning Province (No. 20201slktyb-019). It was also supported in part by the National Science Foundation (NSF) via the Grant Number IIS-1648664. Publisher Copyright: {\textcopyright} 2021, The Author(s).",

year = "2021",

month = dec,

doi = "10.1186/s40854-021-00261-1",

language = "English (US)",

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AU - Guo, Yanhong

AU - Jiang, Shuai

AU - Zhou, Wenjun

AU - Luo, Chunyu

AU - Xiong, Hui

N1 - Funding Information: This research was partially supported by the Natural Science Foundation of China (Nos. 71974031, 71771034), the Chinese Universities Scientific Fund (No. DUT19RW216) and the Economic and Social Development Project of Liaoning Province (No. 20201slktyb-019). It was also supported in part by the National Science Foundation (NSF) via the Grant Number IIS-1648664. Publisher Copyright: © 2021, The Author(s).

PY - 2021/12

Y1 - 2021/12

N2 - 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.

AB - 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.

KW - Lender composition

KW - Loan evaluation

KW - Maturity assessment

KW - P2P lending

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

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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