Generalised additive modelling of the credit risk of Korean personal bank loans

Moffatt, Peter, Kim, Young-Ah and Peters, Simon (2021) Generalised additive modelling of the credit risk of Korean personal bank loans. Journal of Credit Risk. ISSN 1744-6619 (In Press)

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Abstract

We analyze consumer defaults in a sample of 64,000 customers taking personal loans from a Korean bank. Applying a Generalized Additive Modeling (GAM) framework, we show a non-linear impact of loan and borrower characteristics. In particular, the likelihood of default is high for both low income borrowers as well as high income borrowers. Our results are robust to a range of different tests, and highlight the usefulness of the GAM framework, especially the graphical presentation of non-linearities.

Item Type: Article
Uncontrolled Keywords: generalised additive models; b-spline; credit scoring; loan defaults; signal detection theory; mis-classification costs
Faculty \ School: Faculty of Social Sciences > School of Economics
Depositing User: LivePure Connector
Date Deposited: 13 Oct 2021 02:16
Last Modified: 13 Oct 2021 02:16
URI: https://ueaeprints.uea.ac.uk/id/eprint/81675
DOI:

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