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Business model contributions to bank profit performance: A machine learning approach

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  • Bolívar, Fernando
  • Duran, Miguel A.
  • Lozano-Vivas, Ana

Abstract

This paper examines the relation between bank profit performance and business models, using a machine learning–based approach. The analysis contributes to the literature on this relation by considering the bank portfolio’s ability to yield profits as the identification criterion of strategic profiles and by including all the components of the business model simultaneously in the identification process. Our research strategy is applied to the European Union banking system from 1997 to 2021. The paper’s primary finding indicates that specialization seems to be a strategy that results in banks adopting business profiles with better profit performance, particularly if the banks specialize in the standard retail-oriented model.

Suggested Citation

  • Bolívar, Fernando & Duran, Miguel A. & Lozano-Vivas, Ana, 2023. "Business model contributions to bank profit performance: A machine learning approach," Research in International Business and Finance, Elsevier, vol. 64(C).
    • Handle: RePEc:eee:riibaf:v:64:y:2023:i:c:s0275531922002562
    DOI: 10.1016/j.ribaf.2022.101870
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    Keywords

    Bank business models; Cluster analysis; Profitability; Random forest; Tree interpreter;
    All these keywords.

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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