BUSINESS MODELS IN BANKING: A CLUSTER ANALYSIS USING ARCHIVAL DATA

Publikation: Beiträge in ZeitschriftenZeitschriftenaufsätzeForschungbegutachtet

Authors

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.
OriginalspracheEnglisch
ZeitschriftTRAMES-JOURNAL OF THE HUMANITIES AND SOCIAL SCIENCES
Jahrgang23
Ausgabenummer1
Seiten (von - bis)79-107
Anzahl der Seiten29
ISSN1406-0922
DOIs
PublikationsstatusErschienen - 20.03.2019

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© 2019, Estonian Academy Publishers. All rights reserved.

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Forschende

  1. Elena Eckert

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