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Predicting corporate credit risk: Network contagion via trade credit


  • Claudia Berloco
  • Gianmarco De Francisci Morales
  • Daniele Frassineti
  • Greta Greco
  • Hashani Kumarasinghe
  • Marco Lamieri
  • Emanuele Massaro
  • Arianna Miola
  • Shuyi Yang


Trade credit is a payment extension granted by a selling firm to its customer. Companies typically respond to late payments from their customers by delaying payments to suppliers, thus generating a ripple through the transaction network. Therefore, trade credit is as a potential vehicle of propagation of losses in case of default events. The goal of this work is to leverage information on the trade credit among connected firms to predict imminent defaults of firms. We use a unique dataset of client firms of a major Italian bank to investigate firm bankruptcy between October 2016 to March 2018. We develop a model to capture network spillover effects originating from the supply chain on the probability of default of each firm via a sequential approach: the output of a first model component on single firm features is used in a subsequent model which captures network spillovers. While the first component is the standard econometrics way to predict such dynamics, the network module represents an innovative way to look into the effect of trade credit on default probability. This module looks at the transaction network of the firm, as inferred from the payments transiting via the bank, in order to identify the trade partners of the firm. By using several features extracted from the network of transactions, this model is able to predict a large fraction of the defaults, thus showing the value hidden in the network information. Finally, we merge firm and network features with a machine learning model to create a ‘hybrid’ model, which improves the recall for the task by almost 20 percentage points over the baseline.

Suggested Citation

  • Claudia Berloco & Gianmarco De Francisci Morales & Daniele Frassineti & Greta Greco & Hashani Kumarasinghe & Marco Lamieri & Emanuele Massaro & Arianna Miola & Shuyi Yang, 2021. "Predicting corporate credit risk: Network contagion via trade credit," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-29, April.
  • Handle: RePEc:plo:pone00:0250115
    DOI: 10.1371/journal.pone.0250115

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    References listed on IDEAS

    1. Casey, Eddie & O'Toole, Conor M., 2014. "Bank lending constraints, trade credit and alternative financing during the financial crisis: Evidence from European SMEs," Journal of Corporate Finance, Elsevier, vol. 27(C), pages 173-193.
    2. Raymond Fisman & Inessa Love, 2003. "Trade Credit, Financial Intermediary Development, and Industry Growth," Journal of Finance, American Finance Association, vol. 58(1), pages 353-374, February.
    3. Vicente Cuñat, 2007. "Trade Credit: Suppliers as Debt Collectors and Insurance Providers," The Review of Financial Studies, Society for Financial Studies, vol. 20(2), pages 491-527.
    4. Benjamin S. Wilner, 2000. "The Exploitation of Relationships in Financial Distress: The Case of Trade Credit," Journal of Finance, American Finance Association, vol. 55(1), pages 153-178, February.
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    Cited by:

    1. Li, Tangrong & Sun, Xuchu, 2023. "Is controlling shareholders' credit risk contagious to firms? — Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 77(C).

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