ESTONIAN ACADEMY
PUBLISHERS
eesti teaduste
akadeemia kirjastus
PUBLISHED
SINCE 1997
 
TRAMES cover
TRAMES. A Journal of the Humanities and Social Sciences
ISSN 1736-7514 (Electronic)
ISSN 1406-0922 (Print)
Impact Factor (2020): 0.5

BUSINESS MODELS IN BANKING: A CLUSTER ANALYSIS USING ARCHIVAL DATA; pp. 79–107

Full article in PDF format | https://doi.org/10.3176/tr.2019.1.06

Authors
Rainer Lueg, Christian Schmaltz, Modestas Tomkus

Abstract

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.


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