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Do late customer payments impact companies’ probability of default?
[Les retards de paiement des clients impactent-ils la probabilité de défaillance des entreprises ?]

Author

Listed:
  • Michel DIETSCH
  • Olivier GONZALEZ

Abstract

The payment delays granted by suppliers to their customers expose the former to cash flow disruptions, which are aggravated in the event of late payments and may put them in financial difficulty. However, estimating companies’ probability of default using a bankruptcy prediction model shows that the effects of late customer payments are relatively limited. Indeed, while the existence of late customer payments raises a company’s probability of default by 25%, and by 40% if payments are over one month late, deteriorated financial structures increase it by at least a factor of four. Finally, only 8 out of 100 failing companies are potentially exposed to this risk, three-quarters of which owing to late payments over 30 days. Nevertheless, when payments are made increasingly late, all types of companies are affected, regardless of their size, age or financial situation. Les délais de paiement accordés à leurs clients exposent les fournisseurs à des problèmes de trésorerie, aggravés en cas de retards de paiement et susceptibles de les mettre financièrement en difficulté. Pour autant, l’estimation de la probabilité de défaillance d’une entreprise à partir d’un modèle de score montre que les effets de retards de paiement de ses clients restent relativement circonscrits. En effet, si l’existence de retards clients augmente la probabilité de défaillance d’une entreprise de 25%, et de 40% si les retards excèdent un mois, des structures financières dégradées la multiplient au minimum par 4. On estime finalement que seules 8 entreprises défaillantes sur 100 sont potentiellement exposées à ce risque, dont les trois quarts à cause de retards supérieurs à 30 jours. Néanmoins, si les retards prennent de l’ampleur, tous les types d’entreprises sont concernés, quelles que soient leur taille, leur ancienneté ou leur situation financière.

Suggested Citation

  • Michel DIETSCH & Olivier GONZALEZ, 2020. "Do late customer payments impact companies’ probability of default? [Les retards de paiement des clients impactent-ils la probabilité de défaillance des entreprises ?]," Bulletin de la Banque de France, Banque de France, issue 227.
  • Handle: RePEc:bfr:bullbf:2020:227:08
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    References listed on IDEAS

    as
    1. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
    2. Olivier GONZALEZ, 2020. "Les structures de production et les rapports de force figent la situation en matière de délais et de retards de paiement," Bulletin de la Banque de France, Banque de France, issue 227.
    3. Christian Gourieroux & Joann Jasiak, 2007. "Introduction to The Econometrics of Individual Risk: Credit, Insurance, and Marketing," Introductory Chapters, in: The Econometrics of Individual Risk: Credit, Insurance, and Marketing, Princeton University Press.
    4. Edward I. Altman, 1968. "The Prediction Of Corporate Bankruptcy: A Discriminant Analysis," Journal of Finance, American Finance Association, vol. 23(1), pages 193-194, March.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    JEL classification:

    • G20 - Financial Economics - - Financial Institutions and Services - - - General
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • L14 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Transactional Relationships; Contracts and Reputation

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