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Dangerous liasons and hot customers for banks.

Authors :
Cerqueti, Roy
Pampurini, Francesca
Pezzola, Annagiulia
Quaranta, Anna Grazia
Source :
Review of Quantitative Finance & Accounting; Jul2022, Vol. 59 Issue 1, p65-89, 25p
Publication Year :
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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
0924865X
Volume :
59
Issue :
1
Database :
Complementary Index
Journal :
Review of Quantitative Finance & Accounting
Publication Type :
Academic Journal
Accession number :
157686390
Full Text :
https://doi.org/10.1007/s11156-022-01039-x