Evaluating borrowers’ default risk with a spatial probit model reflecting the distance in their relational network

Jong Wook Lee and So Young Sohn

PLOS ONE, 2021, vol. 16, issue 12, 1-11

Abstract: Potential relationship among loan applicants can provide valuable information for evaluating default risk. However, most of the existing credit scoring models either ignore this relationship or consider a simple connection information. This study assesses the applicants’ relation in terms of their distance estimated based on their characteristics. This information is then utilized in a proposed spatial probit model to reflect the different degree of borrowers’ relation on the default prediction of loan applicant. We apply this method to peer-to-peer Lending Club Loan data. Empirical results show that the consideration of information on the spatial autocorrelation among loan applicants can provide high predictive power for defaults.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0261737

DOI: 10.1371/journal.pone.0261737

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