The effect of interfirm financial transactions on the credit risk of small and medium-sized enterprises
Despite the recognized importance of interfirm financial links in determining a company’s performance, only a few studies have incorporated proxies for interfirm links in credit risk models, and none of these use real financial transactions. We estimate a credit risk model for small and medium-sized...
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Veröffentlicht in: | Journal of the Royal Statistical Society. Series A, Statistics in society Statistics in society, 2019-10, Vol.182 (4), p.1205-1226 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Despite the recognized importance of interfirm financial links in determining a company’s performance, only a few studies have incorporated proxies for interfirm links in credit risk models, and none of these use real financial transactions. We estimate a credit risk model for small and medium-sized enterprises, augmented with information on observed interfirm financial transactions. We exploit a novel data set on about 60000 companies based in the UK and their financial transactions over the years 2015 and 2016. We develop several network-augmented credit risk models and compare their prediction performance with that of a conventional credit risk model that includes only a set of financial ratios. We find that augmenting a default risk model with information on the transaction network makes a significant contribution to increasing the default prediction power of risk models built specifically for small and medium-sized enterprises. Our results may help bankers and credit scoring agencies to improve the credit scoring of these companies, ultimately reducing their propensity to apply excessive lending restrictions. |
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ISSN: | 0964-1998 1467-985X |
DOI: | 10.1111/rssa.12500 |