The effect of interfirm financial transactions on the credit risk of small and medium‐sized enterprises. / Vinciotti, Veronica; Tosetti, Elisa; Moscone, Francesco; Lycett, Mark.

In: Journal of the Royal Statistical Society: Series A (Statistics in Society), 24.08.2019, p. 1-22.

Research output: Contribution to journalArticle

E-pub ahead of print
  • Veronica Vinciotti
  • Elisa Tosetti
  • Francesco Moscone
  • Mark Lycett

Abstract

Despite the recognised importance of inter-firm financial links in determining
a company’s performance, only few studies have incorporated proxies for inter-firm links into credit risk models, and none of these use real financial transactions. In this paper, we estimate a credit risk model for small and medium-sized enterprises, augmented with information on observed inter-firm 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 a number of network-augmented credit risk models and compare their prediction performance with that of a conventional credit risk model that only includes 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.
Original languageEnglish
Pages (from-to)1-22
Number of pages22
JournalJournal of the Royal Statistical Society: Series A (Statistics in Society)
Early online date24 Aug 2019
DOIs
Publication statusE-pub ahead of print - 24 Aug 2019
This open access research output is licenced under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.

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