Department of Economics and Business Economics

Business models in banking: A cluster analysis using archival data

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

DOI

  • Rainer Lueg, Leuphana Univ, Leuphana University Luneburg, Inst Finance & Accounting, Univ Southern Denmark, University of Southern Denmark, Dept Econ & Business, Ctr Hlth Econ Res, Econ & Math
  • ,
  • Christian Schmaltz, True North Inst
  • ,
  • Modestas Tomkus, Aarhus Univ, Aarhus University, Dept Econ

We show that clustering can be used to identify bank business models based on variables that proxy how banks create value. Departing from the value proposition and systematically deriving the proxies for value creation link the disconnected 'business model literature' with the 'bank business model literature'. On a sample of 63 large European and U.S. banks, the clustering approach correctly identifies the business model for four out of five banks. In particular, it correctly identifies 100% of all investment banks, 89% of the universal banks, and 44% of the retail banks. Identifying business models is an important preparatory step before implementing business model-specific minimum requirements or assessing the sustainability of business models. Furthermore, a quantitative objective method like clustering is important for regulators because it is a much more economical way to identifying business models than to collect qualitative information about the business model from annual reports.

Original languageEnglish
JournalTrames-Journal of the humanities and social sciences
Volume23
Issue1
Pages (from-to)79-107
Number of pages29
ISSN1406-0922
DOIs
Publication statusPublished - 2019

    Research areas

  • banks, business model, cluster analysis, financial crisis, PERFORMANCE, INNOVATION, CREATION

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ID: 189905955