The major success of fuzzy logic in the field of remote control opened the door to its application in many other fields, including finance. However, there has not been an updated and comprehensive literature review on the uses of fuzzy logic in the financial field. For that reason, this study attempts to critically examine fuzzy logic as an effective, useful method to be applied to financial research and, particularly, to the management of banking crises. The data sources were Web of Science and Scopus, followed by an assessment of the records according to pre-established criteria and an arrangement of the information in two main axes: financial markets and corporate finance. A major finding of this analysis is that fuzzy logic has not yet been used to address banking crises or as an alternative to ensure the resolvability of banks while minimizing the impact on the real economy. Therefore, we consider this article relevant for supervisory and regulatory bodies, as well as for banks and academic researchers, since it opens the door to several new research axes on banking crisis analyses using artificial intelligence techniques.

Until the Great Recession, rescuing banks with taxpayers’ money had been the preferred way to deal with banking crises. The dramatic effects of these practices on the real economy highlighted that bailouts are not a sustainable method to resolve troubled banks going forward. As a result, a new regulatory framework has been proposed, forcing the financial industry to move from “bailout” to “bail-in.” Understanding the implications of such a change is key to ensuring the success of these new banking rules. This article aims to build up a comprehensive and unbiased set of research articles in order to draw conclusions about the current status of the academic literature in the field of capital and loss absorption requirements. A research agenda on the topic is also proposed. The methodological approach undertaken is based on ProKnow-C (Knowledge Development Process-Constructivist). We also contribute to the development of Proknow-C methodology by adding a cross-reference extension to the original framework. The results of our analysis point out that further research has to be undertaken on the subject of loss absorption requirements.

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A successful resolution of a banking entity is linked to the level of capital and loss-absorbing debt instruments available at the time when the resolution is triggered. This article aims to propose an alternative methodology to determine the minimum requirement of loss absorption and recapitalisation capacity for banks. The model proposed uses probability of default and loss given default data together with a series of adjustment factors to estimate the necessary requirement of loss absorption capacity. One of the main advantages of this method is the simplicity and transparency of the model. The second part of this document is focused on applying the methodology proposed to a sample of Spanish banks composed of entities with total assets above EUR200bn. Results of the analysis point out that total loss absorption and recapitalization capacity of 27.5%-34% over risk-weighted assets is desirable. This range is above the current loss absorption requirements set by most of the international regulatory and supervisory bodies. The results presented in this paper are meant to be especially relevant to banking regulators and supervisors, since propose an alternative methodology for calculating the loss absorption requirements.

The Editorial Office did not detect errors in the affiliations and two callouts for Figure 4 on page 11