TY - JOUR

T1 - BUSINESS MODELS IN BANKING: A CLUSTER ANALYSIS USING ARCHIVAL DATA

AU - Lueg, Rainer

AU - Schmaltz, Christian

AU - Tomkus, Modestas

N1 - Publisher Copyright: © 2019, Estonian Academy Publishers. All rights reserved.

PY - 2019/3/20

Y1 - 2019/3/20

N2 - 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.

AB - 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.

KW - banks

KW - business model

KW - cluster analysis

KW - financial crisis

UR - http://www.scopus.com/inward/record.url?scp=85063550861&partnerID=8YFLogxK

U2 - 10.3176/tr.2019.1.06

DO - 10.3176/tr.2019.1.06

M3 - Journal articles

VL - 23

SP - 79

EP - 107

JO - Trames

JF - Trames

SN - 1406-0922

IS - 1

ER -