Cluster Analysis Focusing on the Business Model of European Credit Institutions Based on Data Prior to the Coronavirus Crisis

  • El-Meouch Nedim Márton
doi: 10.32559/et.2021.4.5

Abstract

Following the economic crisis of 2008–2009, Western European banking groups have significantly reduced their presence in the Central and Eastern European region,
which has often been replaced by representatives of the latter region. Based on this rearrangement, the aim of the present research is to cluster European credit institutions
according to their business model using their financial indicators observed before the onset of the coronavirus. Based on the results, the common distinction observed in the literature, the differences between commercial banking operation and the investment banking profile are identified, thus credit institutions are separated in the formed clusters. Institutions in Western Europe and Central and Eastern Europe do not fit strictly into one cluster, but their distribution differs significantly across clusters. The share of credit institutions with foreign parents within groups also differs from the total distribution, and only almost half of the parent and subsidiary bank pairs are included in the same cluster in the analysis.

Keywords:

European credit institutions business model cluster analysis

References

Ayadi, Rym – Emrah Arbak – Willem Pieter De Groen: Business Models In European Banking. Brussels, Centre For European Policy Studies, 2011. Online: http://doi.org/10.2139/ssrn.1945779

Ágoston Kolos Csaba: Klaszterelemzés-előadás. Többváltozós statisztikai modellezés kurzus, Budapesti Corvinus Egyetem, 2016/2017. I. félév.

Erdős Mihály – Mérő Katalin: Pénzügyi közvetítő intézmények. Bankok és intézményi befektetők. Budapest, Akadémiai Kiadó, 2010.

Farné, Matteo – Angelos T. Vouldis: Banks’ Business Models in the Euro Area: A Cluster Analysis in High Dimensions. Annals of Operations Research 305. (2021). 23–57. Online: https://doi.org/10.1007/s10479-021-04045-9

Ferstl, Robert – David Seres: Clustering Austrian Banks’ Business Models and Peer Groups in the European Banking Sector. Oesterreichische Nationalbank (OeNB), Financial Stability Report 24. 2012. december. 79–95. Online: https://www.oenb.at/dam/jcr:9f5fecf1-1624-49ff-8ffd-8a9823115542/fsr_24_special_topics_03_tcm16-252045.pdf

Gál Zoltán: Pénzügyi piacok a globális térben. Budapest, Akadémiai Kiadó, 2010.

Humblot, Thomas: Classification Of European Banks According To Their Business Model. An Objective Approach. BNP Paribas, 2020. július–augusztus. Online: https://bit.ly/3dVO5CW

King, Robert G. – Ross Levine: Finance and Growth: Schumpeter Might be Right. The Quarterly Journal of Economics, 108. (1993a), 3. 717–737. Online: https://doi.org/10.2307/2118406

King, Robert G. – Ross Levine: Finance, Entrepreneurship, and Growth. Theory and Evidence. Journal of Monetary Economics, 32. (1993b), 3. 513–542. Online: https://doi.org/10.1016/0304-3932(93)90028-E

Kovács Erzsébet: Többváltozós adatelemzés. Budapest, Budapesti Corvinus Egyetem – Typotex Kiadó, 2014. Online: https://bit.ly/3pSHTyv

Kutasi, Gábor: Stability of CEE Banks in the Crisis Years. Civic Review, 14. (2018), Special Issue. 241–254. Online: https://doi.org/10.24307/psz.2018.0416

Levine, Ross: The Legal Environment, Banks, and Long-Run Economic Growth. Journal of Money, Credit and Banking, 30. (1998), 3/2. 596–613. Online: https://doi.org/10.2307/2601259

Levine, Ross – Norman Loayza – Thorsten Beck: Financial Intermediation and Growth: Causality and Causes. Journal of Monetary Economics, 46. (2000), 1. 31–77. Online: https://doi.org/10.1016/S0304-3932(00)00017-9

Lucas, André – Julia Schaumburg – Bernd Schwaab: Dynamic Clustering of Multivariate Panel Data. Tinbergen Institute Discussion Paper, 2020-009/III. Online: https://doi.org/10.2139/ssrn.3531721

Marques, Bernardo P. – Carlos F. Alves: Using Clustering Ensemble to Identify Banking Business Models. Intelligent Systems in Accounting, Finance and Management – An International Journal, 27. (2020), 2. 66–94. Online: https://doi.org/10.1002/isaf.1471

Molin, Felix: Cluster Analysis of European Banking Data. Degree Project In Financial Mathematics. KTH Royal Institute, 2017. Online: https://www.math.kth.se/matstat/seminarier/reports/M-exjobb17/171213.pdf

Rousseeuw, Peter J.: Silhouettes. A Graphical Aid to the Interpretation and Validation of Cluster Analysis. Journal of Computational and Applied Mathematics, 20. (1987), november. 53–65. Online: https://doi.org/10.1016/0377-0427(87)90125-7

S&P Capital IQ: SNL Mergers & Acquisitions (2021. október 28). Online: https://doi.org/10.1016/0377-0427(87)90125-7

Vinh, Nguyen Xuan – Julien Epps – James Bailey: Information Theoretic Measures for Clusterings Comparison: Is a Correction for Chance Necessary? In Proceedings of the 26th International Conference on Machine Learning. Montreal, Canada, 2009. 1073–1080. Online: https://doi.org/10.1145/1553374.1553511

Wilkinson, Leland – Laszlo Engelman – James Corter – Mark Coward: Cluster Analysis. In Multivariate Analysis in Psychology and Education Course. University of Illinois Urbana-Champaign, 2012. ősz. Online: http://cda.psych.uiuc.edu/multivariate_fall_2012/systat_cluster_manual.pdf

Downloads

Download data is not yet available.