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.
Cerqueti, R., Pampurini, F., Annagiulia, P., Anna Grazia, Q., Dangerous liasons and hot customers for banks, <<REVIEW OF QUANTITATIVE FINANCE AND ACCOUNTING>>, 2022; (59): 65-89. [doi:10.1007/s11156-022-01039-x] [http://hdl.handle.net/10807/194741]
Dangerous liasons and hot customers for banks
Pampurini, Francesca
Primo
;
2022
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.
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