European banks' business models and their credit risk: A cluster analysis in a high-dimensional context
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In this paper, we investigate the credit risk in the loan portfolio of banks following different business models. We develop a data-driven methodology for identifying the business models of the 365 largest European banks that is suitable for very granular harmonised supervisory data. Our dataset allows us to take into account the full range of the activities in which banks are involved. The proposed method combines in an optimal way data clustering, dimensionality reduction and outlier detection. We identify four business models and exclude as 'outliers' banks that follow idiosyncratic business models. Furthermore, empirical evidence is provided that banks following different business models differ significantly with respect to the credit risk they undertake in their loan portfolios. Traditional commercial banks are characterized by the lowest levels of credit risk while the loan portfolios of securities holding banks are riskier compared to the other banks.
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