Abstract
Risk management has been a topic of great interest to Michael McAleer. Even as recent as 2020, his paper on risk management for COVID-19 was published. In his memory, this article is focused on bankruptcy risk in financial firms. For financial institutions in particular, banks are considered special, given that they perform risk management functions that are unique. Risks in banking arise from both internal and external factors. The GFC underlined the need for comprehensive risk management, and researchers since then have been working towards fulfilling that need. Similarly, the central banks across the world have begun periodic stress-testing of banks’ ability to withstand shocks. This paper investigates the machine-learning and statistical techniques used in the literature on bank failure prediction. The study finds that though considerable progress has been made using advanced statistical and computational techniques, given the complex nature of banking risk, the ability of statistical techniques to predict bank failures is limited. Machine-learning-based models are increasingly becoming popular due to their significant predictive ability. The paper also suggests the directions for future research.
Highlights
This study shows that support vector machines (SVMs) with the Gaussian kernel are capable of extracting useful information from financial data and can be used as part of an early-warning system
The key findings of the paper are that complementing bank-specific vulnerabilities with indicators for macro-financial imbalances and banking sector vulnerabilities improves model performance and yields useful out-of-sample predictions of bank distress during the financial crisis at the time
The findings indicate that the greater the size and the higher the income from nonoperating items and net loans to deposits, the more likely is bank failure; the higher the Interbank ratio, the lower the chances of bank financial distress
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Financial institutions occupy an important position in any economy. Banks in particular perform functions that are unique. Accepting deposits repayable on demand and making loans and investments are the predominant functions that commercial banks perform, besides a host of other functions. Banks accept deposits of short maturity and make loans that have a long maturity. The unique functions that a bank performs expose it to several types of risks, such as interest-rate risk, market risk, credit risk, liquidity risk, off-balance-sheet risk, foreign-exchange risk, and others. Banks are the major users of technology, and they are exposed to technology risk as well as operational risk. Banks’ international lending exposes them to country risk. A combined effect of all these risks could lead to an insolvency risk
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