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Dangerous liasons and hot customers for banks

Author

Listed:
  • Roy Cerqueti

    (Sapienza University of Rome
    London South Bank University)

  • Francesca Pampurini

    (Università Cattolica del Sacro Cuore)

  • Annagiulia Pezzola

    (University of Macerata)

  • Anna Grazia Quaranta

    (University of Macerata)

Abstract

Understanding the correlation between different customers’ loss of creditworthiness is crucial to credit risk analysis. This paper describes a novel method, based on a weighted network model, in which a set of firms, customers of the same bank, represent the nodes while their links and weights derive from the total transaction amounts. We explore the contagion mechanism deriving from the transmission of the difficulties of one customer to other clients of the same bank so highlighting areas where contagion risk is higher. We use a real proprietary data set provided by a bank to illustrate the proposed approach.

Suggested Citation

  • Roy Cerqueti & Francesca Pampurini & Annagiulia Pezzola & Anna Grazia Quaranta, 2022. "Dangerous liasons and hot customers for banks," Review of Quantitative Finance and Accounting, Springer, vol. 59(1), pages 65-89, July.
    • Handle: RePEc:kap:rqfnac:v:59:y:2022:i:1:d:10.1007_s11156-022-01039-x
    DOI: 10.1007/s11156-022-01039-x
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    More about this item

    Keywords

    Credit risk; Systemic risk; Financial network models; Contagion;
    All these keywords.

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • G20 - Financial Economics - - Financial Institutions and Services - - - General
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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