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Some controversial cases of bail-in in the emerging countries have raised the question about whether for those countries to have in place a regulation for the bail-in is appropriate or not. To assess appropriateness, this paper investigates bail-in credibility among investors, as crucial condition for the credibility’s smooth implementation, by measuring the yield spread between bailinable and non-bailinable bonds.

The authors compare the yield spread of banks located in emerging countries that have in place a framework for the bail-in to the comparable yield spread measured for banks located in emerging countries without such framework. The comparison permits to detect whether there is a significant difference between the two spreads, which would suggest that bail-in regulation has been deemed credible by market participants where enforced, or not, which in this case would signal a problem of credibility.

The authors' results point out a significantly higher yield spread for banks located in emerging countries that have adopted a framework for the bail-in of creditors. Bail-in regulation has, therefore, being deemed credible in the adopting emerging countries, thus ensuring a crucial condition for bail-in regulation's smooth application. The authors also point out bank size and country's gross domestic product (GDP) growth as crucial moderators of bail-in expectations of market participants that can guide the implementation of bail-in rules in emerging countries.

This paper contributes to the literature on the credibility of bail-in with a new perspective from the emerging countries.

This paper aims to verify the presence of a management model that confirms or not the one size fits all hypothesis expressed in terms of risk-return. This study will test the existence of stickiness phenomena and discuss the relevance of business model analysis integration with the risk assessment process.

The sample consists of 60 credit institutions operating in Europe for 20 years of observations. This study proposes a classification of banks’ business models (BMs) based on an agglomerative hierarchical clustering algorithm analyzing their performance according to risk and return dimensions. To confirm BM stickiness, the authors verify the tendency and frequency with which a bank migrates to other BMs after exogenous events.

The results show that it is impossible to define a single model that responds to the one size fits all logic, and there is a tendency to adapt the BM to exogenous factors. In this context, there is a propensity for smaller- and medium-sized institutions to change their BM more frequently than larger institutions.

Quantitative metrics seem to be only able to represent partially the intrinsic dynamics of BMs, and to include these metrics, it is necessary to resort to a holistic view of the BM.

This paper provides evidence that BMs’ stickiness indicated in the literature seems to weaken in conjunction with extraordinary events that can undermine institutions’ margins.