European banks’ business models as a driver of strategic planning: one size fits all
| DOI | https://doi.org/10.1108/JFRC-08-2021-0068 |
| Published date | 23 May 2022 |
| Date | 23 May 2022 |
| Pages | 16-39 |
| Subject Matter | Accounting & finance,Financial risk/company failure,Financial compliance/regulation |
| Author | Egidio Palmieri,Enrico Fioravante Geretto,Maurizio Polato |
European banks’business models
as a driver of strategic planning:
one size fits all
Egidio Palmieri,Enrico Fioravante Geretto and Maurizio Polato
Department of Economics and Statistics, University of Udine,
Udine, Italy
Abstract
Purpose –This paper aims to verify the presenceof a management model that confirms or not the one size
fits all hypothesisexpressed in terms of risk-return. This study will test the existenceof stickiness phenomena
and discuss the relevanceof business model analysis integration with the risk assessmentprocess.
Design/methodology/approach –The sample consists of 60 credit institutionsoperating in Europe for
20 years of observations. This study proposesa classification of banks’business models (BMs) based on an
agglomerative hierarchical clustering algorithm analyzing their performance according to risk and return
dimensions. To confirm BM stickiness, the authors verify the tendency and frequency with which a bank
migratesto other BMs after exogenous events.
Findings –The results show that it is impossible to define a single model that responds to the one size
fits all logic, and there is a tendency to adapt the BM to exogenous factors. In this context, there is a
propensity for small er- and medium-sized i nstitutions to chang e their BM more frequent ly than larger
institutions.
Practical implications –Quantitative metrics seem to be only able to represent partially the
intrinsic dynamics of BMs, and to include these metrics, it is necessary to resort to a holistic view of
the BM.
Originality/value –This paper providesevidence that BMs’stickiness indicated in the literature seems to
weaken in conjunctionwith extraordinary events that can undermine institutions’margins.
Keywords Business model, Performance, Bank management, Business model stickiness,
One size fits all, Risk-return
Paper type Research paper
1. Introduction
Recent regulatory innovations aimed at safeguarding the financial system’s stability have
limited the decision-making freedom of institutions, profoundly changing the environment
in which banks operate.This set of constraints has contributed jointly to the macroeconomic
context to the adoption or abandonment of less profitable business models (BMs). This
paper analyzes banks’BMs through quantitativecluster analysis techniques. The business
© Egidio Palmieri, Enrico Fioravante Geretto and Maurizio Polato. Published by Emerald Publishing
Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence.
Anyone may reproduce, distribute, translate and create derivative works of this article (for both
commercial and non-commercial purposes), subject to full attribution to the original publication and
authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/
legalcode
Authors are grateful to the Italian Academic Consortium CRUI and the University of Udine for the
APC voucher aimed at publishing this paper in Open Access format.
JFRC
31,1
16
Received23 August 2021
Revised31 January 2022
12April 2022
Accepted13 April 2022
Journalof Financial Regulation
andCompliance
Vol.31 No. 1, 2023
pp. 16-39
EmeraldPublishing Limited
1358-1988
DOI 10.1108/JFRC-08-2021-0068
The current issue and full text archive of this journal is available on Emerald Insight at:
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model analysis (BMA) represents a valuable tool for regulators to investigate the
institutions’reaction and adaptationto the new set of rules and verify ex post the impact in
terms of profitabilityand risk of the new supervisory framework.
As is known, the BM provides evidence of the company’s competitive advantage over
competitors and how human, material, technological and intangible resources are organized
to achieve the objectives set in strategic planning and risk management. The BMA briefly
considers these qualitative dimensions, which allows a quantitative treatment of these
dimensions and comparabilitybetween institutions.
The interest in BMA has progressively grown over time because of the importance
assumed in the supervisory processes. It represents a valuable tool used by supervisors in
assessing risk exposure and business line vulnerabilities, ensuring a holistic view of risk
management processes (EBA, 2018). This orientation led to the inclusion of BMA in the
Supervisory Review and Evaluation Process (SREP) to assess the sustainability, feasibility
of the BM, exposure and appetite to risks, implementing a forward-looking perspective
(Farnè and Vouldis, 2017;Gualandriand Venturelli, 2020).
Adopting and implementing a BM consistent with the risk profile identified during
strategic planning (also in compliance with the available capital) has strategic importance
for banks’governance. Moreover, external stakeholders could use BMA to identify banks’
competitors according to BM configuration and compare the most profitable bank in terms
of risk-return yieldfor a specific BM.
The interactions among balance sheet items and the existence of unobservable
qualitative characteristics, able to alter BM characteristics, make BMA inefficient in
clustering banks’BMs. Furthermore, this methodology is unsensible to exogenous events
that indirectly affectbalance sheet items and BMs.
This work aims to verify the presence of a management model that expresses
overperformance conditions in terms of risk-return, confirming or not the one size fits all
hypothesis. In addition, we will try to identify the adaptations made to the BM by bank
management in response to external events, therefore verifying the existence of stickiness
phenomena. Finally, the importance of BMA integration with the risk assessment process
will be discussed.
The paper is organized as follows.Section 2 presents an analysis of the literature relating
to the BM in the context of business theory and subsequentlyconcerning the banking sector.
The third paragraph presents the data set and the clustering methodology used. Section 4
identifies and analyzes the four main BMs obtainedthrough the clustering process. Finally,
in Section 5, the conclusions and possiblepaths for further study are presented.
2. Literature review
There is no unique definition of a BM in the literature relatingto business theory. However,
one research stream considers BM as a success factor whose main determinants consist of
policy, governance and assets.According to these variables, it is possible to discriminate the
multiple configurationsof the BM (Wirtz, 2011).
The resource-based view theory offers a different perspective, according to which
business is understood as a combination of resources and skills. The former constitutes the
elementary units of each company, contributing both to objectives achievement, defined in
the strategic planning and performance improvement (Penrose, 1959).For some companies,
typically operating in high-tech sectors, intangible assets play a predominant role in the
BM rather than tangible ones, and this is because of their relevance in the core
business (note that, for other sectors, the role of the two asset classes indicated could
be reversed). According to the perspective under examination, a BM is a valuable tool for
European
banks’
business
models
17
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