How to measure bank credit risk disclosure? Testing a new methodological approach based on the content analysis framework

Enzo Scannella () and Salvatore Polizzi
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Enzo Scannella: University of Palermo
Salvatore Polizzi: University of Palermo

Journal of Banking Regulation, 2021, vol. 22, issue 1, No 6, 73-95

Abstract: Abstract Risk disclosure is a crucial factor in enhancing the efficiency of financial markets and promoting financial stability. This paper proposes a methodological tool to analyze credit risk disclosure in bank financial reports, based on the content analysis framework. The authors also uses this methodology to carry out an empirical study on a small sample of large Italian banks. The paper provides preliminary empirical evidence that banks differ in their credit risk disclosure, even though they are subject to homogeneous regulatory and accounting requirements. Furthermore, by carrying out a correlation-based network analysis, the paper provides preliminary evidence on the existence of a relationship between credit risk disclosure, bank size, and business model. The existing literature has not provided any methodological tool to analyze qualitative and quantitative profiles of bank credit risk disclosure. In order to fill this gap, we propose an original research methodology to investigate bank credit risk reporting. While previous contributions have examined related aspects adopting automated content analysis techniques, this paper proposes an original and non-automated content analysis approach. Our research has several regulatory and strategic implications and lays the foundation for further research in banking, finance, and accounting.

Keywords: Credit risk; Risk reporting; Risk disclosure; Risk management; Banking (search for similar items in EconPapers)
JEL-codes: G18 G2 G21 G24 G28 G32 (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (3)

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DOI: 10.1057/s41261-020-00129-x

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