Business Model Contributions to Bank Profit Performance: A Machine Learning Approach

Fernando Bolívar, Miguel A. Duran, Ana Lozano-Vivas
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引用次数: 2

Abstract

This paper analyzes the relation between bank profit performance and business models. To assess the profitability of bank business models, we propose a new approach based on machine learning. In particular, we identify bank business models using balance sheet components’ contributions to profitability as a grouping criterion. Thus, in contrast to previous works, the strategy for identifying bank business models is not based on similarities among banks’ asset and liability mixes, but on these mixes’ contributions to profitability. We apply this methodological proposal to the European Union banking system in 1997–2016.
商业模式对银行利润表现的贡献:一种机器学习方法
本文分析了银行利润绩效与商业模式之间的关系。为了评估银行业务模式的盈利能力,我们提出了一种基于机器学习的新方法。特别是,我们使用资产负债表组件对盈利能力的贡献作为分组标准来确定银行业务模型。因此,与以前的工作相反,识别银行业务模式的策略不是基于银行资产和负债组合之间的相似性,而是基于这些组合对盈利能力的贡献。我们将这一方法建议应用于1997-2016年的欧盟银行体系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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