EconPapers    
Economics at your fingertips  
 

Which financial indicators do stakeholders have to focus on to manage risk of bank failure?

Zinaba Atman and Eric Lamarque

Review of Accounting and Finance, 2025, vol. 24, issue 4, 503-550

Abstract: PurposeThis study aims to examine the informational content of financial disclosures from banks to identify the determinants that enable stakeholders and regulators to prevent the risk of bank failure.Design/methodology/approachThis study is based on European bank database from 2010 to 2021. The authors classified the variables into groups based on their nature. Z-score return on assets (ROA) and Z-score return on risk-weighted assets (RORWA) were used to test these determinants. This study used the least absolute shrinkage and selection operator and applied the approaches proposed by Ahrens et al. (2020). The selected indicators were analysed using the theoretical framework of positive and normative accounting theories.FindingsA selection of indicators from four groups of variables stands out because of their high coefficients in all samples: financial instruments, income statement impact, loan quality and macroeconomic variables. The selected groups of indicators are similar for all banks. However, the indicators selected to identify banking distress vary according to bank category (global systemically important banks (G-SIBs), domestic systemically important banks (D-SIBs) and financial conglomerates (FICO)). This study shows the importance of investment portfolio risk management and its impact on bank performance. Secondly, it highlights the informative value of the loan loss provisioning indicator and the default rate introduced by International Financial Reporting Standards 9. Finally, this study discusses the role of financial information and accounting standards theory as a decision-making tool for future activities.Originality/valueThis study is among the few to study the impact of financial distress in Europe during the study period using big data from Pillar 3 bank reports and machine learning methods.

Keywords: Accounting theory; Pillar 3; Risk disclosure; Information content; Financial distress; LASSO; Z-score ROA; Z-score RORWA (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.emerald.com/raf/article/24/4/503/12557 ... stakeholders-have-to (text/html)
https://www.emerald.com/raf/article-pdf/24/4/503/10056414/raf-04-2024-0155en.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eme:rafpps:raf-04-2024-0155

DOI: 10.1108/RAF-04-2024-0155

Access Statistics for this article

Review of Accounting and Finance is currently edited by Nawazish Mirza

More articles in Review of Accounting and Finance from Emerald Group Publishing Limited
Bibliographic data for series maintained by Emerald Support ().

 
Page updated 2026-11-04
Handle: RePEc:eme:rafpps:raf-04-2024-0155