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Heterogeneity of business models and banking sector resilience

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Abstract

This paper studies the relationship between the heterogeneity of business models and the banking sector's resilience, in light of the interplay between diversification, market power, and resilience. Our goal is to tackle the open puzzle related to the effects of diversification-induced homogeneity of banks' business models on the banking sector's stability. Using a sample of 1268 banks from 33 countries (Europe, Asia, America), for the period between 2005 and 2021, we estimate a 3SLS model that accounts for the interplay between revenue diversification, heterogeneity, market power and resilience. We apply principal components and clustering analysis to identify the banks' business models and compute an ecology-based measure of heterogeneity per country. We find that revenue diversification reduces bank heterogeneity, suggesting that banks pursue uniform diversification strategies. We also uncover a positive relationship between bank heterogeneity and market power, suggesting low rivalry among different business models. Importantly, our results indicate that bank heterogeneity positively impacts resilience and is economically significant. Namely, we estimate a 4.5% increase in the Z-score due to a one (within) standard deviation increase in business model heterogeneity. We discuss several implications of our results for micro- and macro-prudential supervision and regulation, and identify potential avenues for future research.

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Notes

  1. According to Porter [16], ‘strategic groups’ represent set of firms operating in a given market that have made similar decisions regarding certain long-term strategic dimensions (e.g. distribution channel, value chain integration, geographical reach).

  2. Notably, the literature on business model classification has developed significantly in recent years, wherein two techniques stand out: dimensionality reduction [9, 11] and clustering analysis [10, 14, 42, 43]. The methodology we follow in this paper can best be described as a combination of dimensionality reduction and clustering analysis. For a detail description of the method, see Marques & Alves [12].

  3. The final list of countries includes 17 from Europe (Austria, Belgium, Czech Republic, France, Germany, Ireland, Italy, Luxembourg, the Netherlands, Norway, Poland, Portugal, Russia, Spain, Switzerland, Turkey, United Kingdom), 11 from Asia (Australia, China, Hong Kong, India, Indonesia, Japan, Korea, Malaysia, Philippines, Thailand, Vietnam) and 5 from America (Brazil, Chile, Colombia, Mexico, United States).

  4. The auxiliary results that support the findings of an optimal partition of four clusters (e.g. Calinski-Harabasz Index) are available in the supplementary materials.

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Funding

This research has been financed by European Union and Portuguese public funds through the FCT (Fundação para a Ciência e a Tecnologia, I.P.) and the European Social Funds (Operational Program Norte 2020) under projects number UIDB/04105/2020 (CEF.UP) and UIDB/00731/2020 (CEGE).

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  1. Universidade Católica Portuguesa, Católica Porto Business School, Research Centre in Management and Economics, Porto, Portugal

    Bernardo P. Marques

  2. Universidade do Porto, Faculty of Economics, CEF.UP, Porto, Portugal

    Carlos F. Alves

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  1. Bernardo P. Marques
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Correspondence to Bernardo P. Marques.

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Marques, B.P., Alves, C.F. Heterogeneity of business models and banking sector resilience. J Bank Regul (2023). https://doi.org/10.1057/s41261-023-00227-6

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