Journals / Politik Ekonomik Kuram / 2026 / Cilt: 9 Sayı: 3

The Impact of Bank Business Model Similarity on Systemic Risk: The European Case

Bankaların İş Modellerindeki Benzerliğin Sistemik Riske Etkisi: Avrupa Örneği

Lütfi Öztürker(MARMARA ÜNİVERSİTESİ)0000-0002-6959-3460
Murat Akbalık(MARMARA ÜNİVERSİTESİ)0000-0002-7955-3630
Pages
877–901
Publication Date
2025-09-19
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The findings indicate that beyond the standalone effects of business model similarity and diversification levels, their interactions with each other and with bank size play a critical role in understanding systemic risk dynamics.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This study analyzes the impact of three key elements derived from the balance sheets of European banks on systemic risk.
📊
Key Findings & Data:Regression analyses conducted on a panel dataset including 165 publicly traded banks from 25 European countries reveal how classifications based on bank size (too-big-to-fail and others) conditionally regulate the interactive effects on systemic risk.
💡
Conclusion & Impact:The findings indicate that beyond the standalone effects of business model similarity and diversification levels, their interactions with each other and with bank size play a critical role in understanding systemic risk dynamics.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Sistemik risk · benzerlik · çeşitlendirme

Abstract

This study analyzes the impact of three key elements derived from the balance sheets of European banks on systemic risk. These elements are the status of being too-big-to-fail or not, the levels of diversification across asset and liability items, and the similarity of a bank’s business model to those of other banks. In this context, the research seeks to address the following key questions: How do similarity and diversification influence systemic risk, and how do they interact with each other? How do these relationships differ between too-big-to-fail banks and others? How do the interactions between similarity, diversification, and size shape systemic risk? Regression analyses conducted on a panel dataset including 165 publicly traded banks from 25 European countries reveal how classifications based on bank size (too-big-to-fail and others) conditionally regulate the interactive effects on systemic risk. The findings indicate that beyond the standalone effects of business model similarity and diversification levels, their interactions with each other and with bank size play a critical role in understanding systemic risk dynamics. Specifically, it is found that for too-big-to-fail banks, similarity increases systemic risk, asset diversification decreases it, and liability diversification increases it. For other banks, these dynamics exhibit opposite effects, except for liability diversification. In this context, it is emphasized that ensuring financial stability requires optimizing business model similarity and diversification levels based on bank size and country-specific economic conditions. The study highlights the need for a more comprehensive approach to reassess Basel regulations in the context of systemic risk and offers practical recommendations for policymakers at both micro and macro levels.

Özet

Bu çalışma, Avrupa bankalarının bilançolarından türetilen üç ana unsurun sistemik risk üzerindeki etkilerini analiz etmektedir. Bu unsurlar, batmayacak kadar büyük olup olmama durumu, aktif ve pasif kalemler bazında yapılan çeşitlendirmenin düzeyleri ile iş modelinin diğer bankalarınkine benzerliğidir. Bu çerçevede araştırma, aşağıdaki temel sorulara yanıt aramaktadır: Benzerlik ve çeşitlendirme, sistemik riski nasıl etkiler ve birbirleriyle nasıl etkileşime girer? Bu ilişkiler, batmayacak kadar büyük bankalar ile diğer bankalar için nasıl farklılık gösterir? Benzerlik, çeşitlendirme ve büyüklük arasındaki etkileşimler, sistemik riski nasıl şekillendirir? 25 Avrupa ülkesinden 165 halka açık bankayı içeren panel veri seti üzerinde yapılan regresyon analizleri, bankalar arasında büyüklüğe göre yapılan sınıflandırmaların (batmayacak kadar büyük ve diğerleri) sistemik risk üzerindeki etkileşimli etkileri nasıl düzenlediğini ortaya koymaktadır. Bulgular, iş modeli benzerliğinin ve çeşitlendirme düzeylerinin tek başına etkilerinin ötesinde, bu değişkenlerin birbirleriyle ve banka büyüklüğüyle olan etkileşimlerinin sistemik risk dinamiklerini anlamada kritik rol oynadığını göstermektedir. Özellikle, batmayacak kadar büyük bankalarda benzerliğin sistemik riski artırdığı, aktif çeşitlendirmesinin azalttığı ve pasif çeşitlendirmesinin artırdığı bulunmuştur. Diğer bankalarda ise bu dinamiklerin, pasif çeşitlendirmesi hariç olmak üzere, ters yönde etkiler gösterdiği ortaya konulmuştur. Bu bağlamda, finansal istikrarın sağlanabilmesi için iş modeli benzerliği ile çeşitlendirme düzeylerinin banka büyüklüğü ve ülkeye özgü ekonomik koşullara göre optimize edilmesi gerektiği vurgulanmaktadır. Çalışma, Basel regülasyonlarının sistemik risk bağlamında daha kapsamlı bir yaklaşımla yeniden değerlendirilmesi gerektiğine işaret etmekte ve politika yapıcılar için hem mikro hem de makro düzeyde uygulanabilir öneriler sunmaktadır.

🔖

Cite This Article

Öztürker, L., Akbalık, M. (2025). The Impact of Bank Business Model Similarity on Systemic Risk: The European Case. Politik Ekonomik Kuram, Cilt: 9 Sayı: 3, 877–901. https://doi.org/10.30586/pek.1607691

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (39)

  1. Acharya, V. V. (2009). A theory of systemic risk and design of prudential bank regulation. Journal of financial stability, 5(3), 224-255. https://doi.org/10.1016/j.jfs.2009.02.001
  2. Acharya, V. V., Pedersen, L. H., Philippon, T., & Richardson, M. (2017). Measuring systemic risk. The review of financial studies, 30(1), 2-47. https://doi.org/10.1093/rfs/hhw088
  3. Acharya, V. V., Pedersen, L., Philippon, T., & Richardson, M. (2009). Regulating systemic risk. Restoring financial stability: How to repair a failed system, 283-304. https://pages.stern.nyu.edu/~sternfin/vacharya/public_html/acharya_philippon_richardson_nber.pdf
  4. Acharya, V. V., & Yorulmazer, T. (2007). Too many to fail—An analysis of time-inconsistency in bank closure policies. Journal of financial intermediation, 16(1), 1-31. https://doi.org/10.1016/j.jfi.2006.06.001
  5. Adrian, T., & Brunnermeier, M. K. (2016). CoVaR. The American Economic Review, 106(7), 1705–1741. https://doi.org/10.1257/aer.20120555
  6. Allen, F., Babus, A., & Carletti, E. (2012). Asset commonality, debt maturity and systemic risk. Journal of Financial Economics, 104(3), 519-534. https://doi.org/10.1016/j.jfineco.2011.07.003
  7. Ayadi, R., Arbak, E., & Pieter De Groen, W. (2012). Regulation of European banks and business models: towards a new paradigm?. Centre for European Policy Studies, Forthcoming. https://www.ceps.eu/ceps-publications/regulation-european-banks-and-business-models-towards-new-paradigm/
  8. Ayadi, R., Bongini, P., Casu, B., & Cucinelli, D. (2021). Bank business model migrations in Europe: Determinants and effects. British Journal of Management, 32(4), 1007–1026. https://doi.org/10.1111/1467-8551.12437
  9. Ayres, I., & Mitts, J. (2015). Anti-herding regulation. Harvard Business Law Review, 5(1), 1–34. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2399240
  10. Bandt, O. D., Hartmann, P., & Peydró, J. L. (2010). Systemic risk in banking: An update. https://global.oup.com/academic/product/the-oxford-handbook-of-banking-9780199688500?cc=nl&lang=en&
  11. Barron, J. M., & Valev, N. T. (2000). International lending by U.S. banks. Journal of Money, Credit and Banking, 32(3), 357–381. https://doi.org/10.2307/2601170
  12. Borio, C. (2003). Towards a macroprudential framework for financial supervision and regulation? CESifo Economic Studies, 49(2), 181–215. https://doi.org/10.1093/cesifo/49.2.181
  13. Bräuning, F., & Fillat, J. L. (2020). The impact of regulatory stress tests on bank lending and its macroeconomic consequences. Federal Reserve Bank of Boston Working Papers. https://www.bostonfed.org/publications/research-department-working-paper/2020/the-impact-of-regulatory-stress-tests-on-bank-lending-and-its-macroeconomic-consequences.aspx
  14. Caccioli, F., Shrestha, M., Moore, C., & Farmer, J. D. (2014). Stability analysis of financial contagion due to overlapping portfolios. Journal of Banking & Finance, 46, 233–245. https://doi.org/10.1016/j.jbankfin.2014.05.021
  15. Cai, J. (2022). Bank herding and systemic risk. Economic Systems, 46(4), 101042. https://doi.org/10.1016/j.ecosys.2022.101042
  16. Coelho, R., & Restoy, F. (2024). Capital buffers and the micro-macro nexus (FSI Briefs No. 24). Financial Stability Institute. https://www.bis.org/fsi/fsibriefs24.htm
  17. Delpini, D., Battiston, S., Riccaboni, M., Gabbi, G., Pammolli, F., & Caldarelli, G. (2019). Systemic risk from investment similarities. PLoS One, 14(5), e0217141. https://doi.org/10.1371/journal.pone.0217141
  18. Deb, P., Norton, E. C., & Manning, W. G. (2017). Health econometrics using Stata (Vol. 3). Stata Press. https://www.surveydesign.com.au/preview/heus-preview.pdf?srsltid=AfmBOoo7RqQ8blqrur2tmNgtA_sVu-OU7RCqGBVc3zUJirNUXZCwsS5b
  19. Espinosa-Vega, M. A., Kahn, C. M., & Sole, J. (2010). Systemic risk and the redesign of financial regulation. IMF Global Financial Stability Report. https://doi.org/10.5089/9781589069169.082
  20. Galati, G., & Moessner, R. (2013). Macroprudential policy–a literature review. Journal of Economic Surveys, 27(5), 846–878. https://doi.org/10.1111/j.1467-6419.2012.00729.x
  21. Gavriilidis, K., Kallinterakis, V., & Ferreira, M. P. L. (2013). Institutional industry herding: Intentional or spurious? Journal of International Financial Markets, Institutions & Money, 26, 192–214. https://doi.org/10.1016/j.intfin.2013.05.008
  22. Goldstein, I., Kopytov, A., Shen, L., & Xiang, H. (2024). Bank heterogeneity and financial stability. Journal of Financial Economics, 162, 103934. https://doi.org/10.1016/j.jfineco.2024.103934
  23. Greenwood, R., Landier, A., & Thesmar, D. (2015). Vulnerable banks. Journal of Financial Economics, 115(3), 471–485. https://doi.org/10.1016/j.jfineco.2014.11.006
  24. Heo, Y. (2019). The impact of bank herding on systemic risk. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3366128
  25. Horváth, B. L., & Wagner, W. (2017). The disturbing interaction between countercyclical capital requirements and systemic risk. Review of Finance, 21(4), 1485–1511. https://doi.org/10.1093/rof/rfx001
  26. Ibragimov, R., Jaffee, D., & Walden, J. (2011). Diversification disasters. Journal of Financial Economics, 99(2), 333–348. https://doi.org/10.1016/j.jfineco.2010.08.015
  27. IMF (International Monetary Fund) (2011). Macroprudential Policy: An Organizing Framework1. https://www.imf.org/external/np/pp/eng/2011/031411.pdf
  28. Kaufman, G. G., & Scott, K. E. (2003). What is systemic risk, and do bank regulators retard or contribute to it?. The independent review, 7(3), 371-391. https://www.independent.org/publications/tir/article.asp?id=88
  29. Kingsley, A. F., Noordewier, T. G., & van den Bergh, R. G. (2017). Overstating and understating interaction results in international business research. Journal of World Business, 52(2), 286–295. https://doi.org/10.1016/j.jwb.2016.12.010
  30. Lee, C.-C., Chen, P.-F., & Zeng, J.-H. (2020). Bank income diversification, asset correlation, and systemic risk. South African Journal of Economics, 88(1), 71–89. https://doi.org/10.1111/saje.12235
  31. Leeper, T. J. (2017). Interpreting regression results using average marginal effects with R’s margins. Comprehensive R Archive Network (CRAN). https://www.semanticscholar.org/paper/Interpreting-Regression-Results-using-Average-with-Leeper/9615c76bd5d81f7ebbbdac9714619863dc3a2337
  32. Raffestin, L. (2014). Diversification and systemic risk. Journal of Banking & Finance, 46, 85–106. https://doi.org/10.1016/j.jbankfin.2014.05.014
  33. Saunders, A., Schmid, M., & Walter, I. (2020). Strategic scope and bank performance. Journal of Financial Stability, 46, 100715. https://doi.org/10.1016/j.jfs.2019.100715
  34. Stiroh, K. J. (2018). Supervisory implications of rising similarity in banking: Remarks at the Financial Times US Banking Forum: Charting a Course for Stability and Success, New York City. Federal Reserve Bank of New York. https://www.newyorkfed.org/newsevents/speeches/2018/sti181101
  35. Suh, S. (2019). Asset correlation and bank capital regulation: A macroprudential perspective. International Review of Economics & Finance, 62, 355–378. https://doi.org/10.1016/j.iref.2019.04.006
  36. Wagner, W. (2010). Diversification at financial institutions and systemic crises. Journal of Financial Intermediation, 19(3), 373–386. https://doi.org/10.1016/j.jfi.2009.07.002
  37. Wagner, W. (2011). Systemic liquidation risk and the diversity–diversification trade‐off. The Journal of Finance, 66(4), 1141–1175. https://doi.org/10.1111/j.1540-6261.2011.01666.x
  38. Ward, J. H. Jr. (1963). Hierarchical grouping to optimize an objective function. Journal of the American Statistical Association, 58(301), 236–244. https://doi.org/10.1080/01621459.1963.10500845
  39. Yang, H. F., Liu, C. L., & Chou, R. Y. (2020). Bank diversification and systemic risk. The Quarterly Review of Economics and Finance, 77, 311–326. https://doi.org/10.1016/j.qref.2019.11.003