Dangerous liasons and hot customers for banks

Roy Cerqueti (), Francesca Pampurini (), Annagiulia Pezzola () and Anna Grazia Quaranta ()
Additional contact information
Roy Cerqueti: Sapienza University of Rome
Francesca Pampurini: Università Cattolica del Sacro Cuore
Annagiulia Pezzola: University of Macerata
Anna Grazia Quaranta: University of Macerata

Review of Quantitative Finance and Accounting, 2022, vol. 59, issue 1, No 3, 65-89

Abstract: 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.

Keywords: Credit risk; Systemic risk; Financial network models; Contagion (search for similar items in EconPapers)
JEL-codes: C02 G20 G21 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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DOI: 10.1007/s11156-022-01039-x

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