IDEAS home Printed from https://ideas.repec.org/a/eee/reveco/v98y2025ics1059056025001145.html
   My bibliography  Save this article

Tailored microprudential recommendations for bank profit retention using a risk tolerance framework

Author

Listed:
  • Jakubik, Petr
  • Moinescu, Bogdan Gabriel

Abstract

This study presents a tailored microprudential approach to profit retention by reversing bank failure prediction models within a risk tolerance framework. Using a dataset of approximately 700 European commercial banks from 2012 to 2022, including around 30 failed institutions identified by the European Banking Authority based on notifications of resolution cases and liquidations involving deposit guarantee funds, the research develops several early warning models. These models integrate macrofinancial stress indicators, bank-specific intermediation measures, financial control variables, and capital buffers. The aim is to align prudential expectations for dividend payout ratios with each bank's risk profile, derived from distress probability models. The results propose that banks' dividend policies should be adjusted based on their capital adequacy and failure likelihood, offering a dynamic and risk-based approach to profit retention. These insights are critical for policymakers, supervisors, and bank managers focused on maintaining financial stability and optimizing prudential buffers, while allowing for more flexible capital planning tailored to macroeconomic conditions.

Suggested Citation

  • Jakubik, Petr & Moinescu, Bogdan Gabriel, 2025. "Tailored microprudential recommendations for bank profit retention using a risk tolerance framework," International Review of Economics & Finance, Elsevier, vol. 98(C).
    • Handle: RePEc:eee:reveco:v:98:y:2025:i:c:s1059056025001145
    DOI: 10.1016/j.iref.2025.103951
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1059056025001145
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.iref.2025.103951?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Petr Jakubik & Bogdan Gabriel Moinescu, 2023. "What is the optimal capital ratio implying a stable European banking system?," International Finance, Wiley Blackwell, vol. 26(3), pages 324-343, December.
    2. Lepetit, Laetitia & Strobel, Frank, 2015. "Bank insolvency risk and Z-score measures: A refinement," Finance Research Letters, Elsevier, vol. 13(C), pages 214-224.
    3. David Miles & Jing Yang & Gilberto Marcheggiano, 2011. "Optimal Bank Capital," Discussion Papers 31, Monetary Policy Committee Unit, Bank of England.
    4. Anginer, Deniz & Bertay, Ata Can & Cull, Robert & Demirgüç-Kunt, Asli & Mare, Davide S., 2024. "Bank capital regulation and risk after the Global Financial Crisis," Journal of Financial Stability, Elsevier, vol. 74(C).
    5. Claudia M. Buch & Benjamin Weigert, 2019. "Macroprudential policy in a currency union," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 155(1), pages 23-33, February.
    6. Mr. Tigran Poghosyan & Mr. Martin Cihak, 2009. "Distress in European Banks: An Analysis Basedon a New Dataset," IMF Working Papers 2009/009, International Monetary Fund.
    7. Vincent BouvatierBy, 2017. "The frequency of banking crises in a dynamic setting: a discrete-time duration approach," Oxford Economic Papers, Oxford University Press, vol. 69(4), pages 1078-1100.
    8. Cihak, Martin & Demirgüç-Kunt, Asli & Martinez Peria, Maria Soledad & Mohseni-Cheraghlou, Amin, 2013. "Bank regulation and supervision in the context of the global crisis," Journal of Financial Stability, Elsevier, vol. 9(4), pages 733-746.
    9. Davis, E. Philip & Karim, Dilruba, 2008. "Comparing early warning systems for banking crises," Journal of Financial Stability, Elsevier, vol. 4(2), pages 89-120, June.
    10. Iwanicz-Drozdowska, Małgorzata & Witkowski, Bartosz, 2022. "Regulation and supervision of the European banking industry. Does one size fit all?," Journal of Policy Modeling, Elsevier, vol. 44(1), pages 113-129.
    11. Alan Greenspan, 1998. "The role of capital in optimal banking supervision and regulation," Economic Policy Review, Federal Reserve Bank of New York, vol. 4(Oct), pages 163-168.
    12. Detken, Carsten & Peltonen, Tuomas A. & Schudel, Willem & Behn, Markus, 2013. "Setting countercyclical capital buffers based on early warning models: would it work?," Working Paper Series 1604, European Central Bank.
    13. Anani, Makafui & Owusu, Felix, 2023. "Regulatory capital and bank risk-resilience amid the Covid-19 pandemic: How are the Basel reforms faring?," Finance Research Letters, Elsevier, vol. 52(C).
    14. Rebel Cole & Lawrence White, 2012. "Déjà Vu All Over Again: The Causes of U.S. Commercial Bank Failures This Time Around," Journal of Financial Services Research, Springer;Western Finance Association, vol. 42(1), pages 5-29, October.
    15. Betz, Frank & Oprică, Silviu & Peltonen, Tuomas A. & Sarlin, Peter, 2014. "Predicting distress in European banks," Journal of Banking & Finance, Elsevier, vol. 45(C), pages 225-241.
    16. Tânia Costa & Júlio Lobão & Luís Pacheco, 2023. "Reassessing bank monitoring models: an empirical analysis of the value of market signals in the period 2008–2020," Journal of Banking Regulation, Palgrave Macmillan, vol. 24(2), pages 206-227, June.
    17. Petropoulos, Anastasios & Siakoulis, Vasilis & Stavroulakis, Evangelos & Vlachogiannakis, Nikolaos E., 2020. "Predicting bank insolvencies using machine learning techniques," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1092-1113.
    18. Leonardo Gambacorta & Sudipto Karmakar, 2018. "Leverage and Risk-Weighted Capital Requirements," International Journal of Central Banking, International Journal of Central Banking, vol. 14(5), pages 153-191, December.
    19. Citterio, Alberto, 2024. "Bank failure prediction models: Review and outlook," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).
    20. Miller, Scott & Olson, Eric & Yeager, Timothy J., 2015. "The relative contributions of equity and subordinated debt signals as predictors of bank distress during the financial crisis," Journal of Financial Stability, Elsevier, vol. 16(C), pages 118-137.
    21. Iana Liadze & Ray Barrell & Professor E. Philip Davis, 2010. "Calibrating macroprudential policy," National Institute of Economic and Social Research (NIESR) Discussion Papers 354, National Institute of Economic and Social Research.
    22. Lang, Jan Hannes & Peltonen, Tuomas A. & Sarlin, Peter, 2018. "A framework for early-warning modeling with an application to banks," Working Paper Series 2182, European Central Bank.
    23. Demyanyk, Yuliya & Hasan, Iftekhar, 2010. "Financial crises and bank failures: A review of prediction methods," Omega, Elsevier, vol. 38(5), pages 315-324, October.
    24. ., 2012. "Towards a Measure of Financial Fragility," Chapters, in: Financial Stability in Practice, chapter 11, pages 213-250, Edward Elgar Publishing.
    25. Riccardo Lisa & Stefano Zedda & Francesco Vallascas & Francesca Campolongo & Massimo Marchesi, 2011. "Modelling Deposit Insurance Scheme Losses in a Basel 2 Framework," Journal of Financial Services Research, Springer;Western Finance Association, vol. 40(3), pages 123-141, December.
    26. Li Xian Liu & Shuangzhe Liu & Milind Sathye, 2021. "Predicting Bank Failures: A Synthesis of Literature and Directions for Future Research," JRFM, MDPI, vol. 14(10), pages 1-24, October.
    27. David Miles & Jing Yang & Gilberto Marcheggiano, 2013. "Optimal Bank Capital," Economic Journal, Royal Economic Society, vol. 123(567), pages 1-37, March.
    28. Campbell, Gareth & Coyle, Christopher & Turner, John D., 2016. "This time is different: Causes and consequences of British banking instability over the long run," Journal of Financial Stability, Elsevier, vol. 27(C), pages 74-94.
    29. Barth, James R. & Miller, Stephen Matteo, 2018. "Benefits and costs of a higher bank “leverage ratio”," Journal of Financial Stability, Elsevier, vol. 38(C), pages 37-52.
    30. Iana Liadze & Ray Barrell & Professor E. Philip Davis, 2010. "Calibrating macroprudential policy," National Institute of Economic and Social Research (NIESR) Discussion Papers 354, National Institute of Economic and Social Research.
    31. Beutel, Johannes & List, Sophia & von Schweinitz, Gregor, 2019. "Does machine learning help us predict banking crises?," Journal of Financial Stability, Elsevier, vol. 45(C).
    32. Asli Demirgüç-Kunt & Enrica Detragiache, 1998. "The Determinants of Banking Crises in Developing and Developed Countries," IMF Staff Papers, Palgrave Macmillan, vol. 45(1), pages 81-109, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Petr Jakubik & Bogdan Gabriel Moinescu, 2023. "What is the optimal capital ratio implying a stable European banking system?," International Finance, Wiley Blackwell, vol. 26(3), pages 324-343, December.
    2. Fendel Ralf & Stremmel Hanno, 2016. "Characteristics of Banking Crises: A Comparative Study with Geographical Contagion," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 236(3), pages 349-388, May.
    3. repec:erf:erfstu:78 is not listed on IDEAS
    4. Lanbiao Liu & Chen Chen & Bo Wang, 2022. "Predicting financial crises with machine learning methods," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(5), pages 871-910, August.
    5. Kristóf, Tamás & Virág, Miklós, 2022. "EU-27 bank failure prediction with C5.0 decision trees and deep learning neural networks," Research in International Business and Finance, Elsevier, vol. 61(C).
    6. Fabrizio Ferriani & Wanda Cornacchia & Paolo Farroni & Eliana Ferrara & Francesco Guarino & Francesco Pisanti, 2019. "An early warning system for less significant Italian banks," Questioni di Economia e Finanza (Occasional Papers) 480, Bank of Italy, Economic Research and International Relations Area.
    7. Citterio, Alberto, 2024. "Bank failure prediction models: Review and outlook," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).
    8. Tölö, Eero, 2020. "Predicting systemic financial crises with recurrent neural networks," Journal of Financial Stability, Elsevier, vol. 49(C).
    9. Parnes, Dror & Gormus, Alper, 2024. "Prescreening bank failures with K-means clustering: Pros and cons," International Review of Financial Analysis, Elsevier, vol. 93(C).
    10. Raphaël Cardot-Martin & Fabien Labondance & Catherine Refait-Alexandre, 2022. "Capital ratios and banking crises in the European Union," International Economics, CEPII research center, issue 172, pages 389-402.
    11. Betz, Frank & Oprică, Silviu & Peltonen, Tuomas A. & Sarlin, Peter, 2014. "Predicting distress in European banks," Journal of Banking & Finance, Elsevier, vol. 45(C), pages 225-241.
    12. Manthoulis, Georgios & Doumpos, Michalis & Zopounidis, Constantin & Galariotis, Emilios, 2020. "An ordinal classification framework for bank failure prediction: Methodology and empirical evidence for US banks," European Journal of Operational Research, Elsevier, vol. 282(2), pages 786-801.
    13. Quentin Bro de Comères, 2022. "Predicting European Banks Distress Events: Do Financial Information Producers Matter?," Working Papers hal-03752678, HAL.
    14. D. Fernández-Arias & M. López-Martín & T. Montero-Romero & F. Martínez-Estudillo & F. Fernández-Navarro, 2018. "Financial Soundness Prediction Using a Multi-classification Model: Evidence from Current Financial Crisis in OECD Banks," Computational Economics, Springer;Society for Computational Economics, vol. 52(1), pages 275-297, June.
    15. Fiordelisi, Franco & Mare, Davide Salvatore, 2013. "Probability of default and efficiency in cooperative banking," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 26(C), pages 30-45.
    16. Jorge E. Galán, 2021. "CREWS: a CAMELS-based early warning system of systemic risk in the banking sector," Occasional Papers 2132, Banco de España.
    17. de-Ramon, Sebastián & Iscenko, Zanna & Osborne, Matthew & Straughan, Michael & Andrews, Peter, 2012. "Measuring the impact of prudential policy on the macroeconomy: A practical application to Basel III and other responses to the financial crisis," MPRA Paper 69423, University Library of Munich, Germany.
    18. Savas Papadopoulos & Pantelis Stavroulias & Thomas Sager, 2019. "Systemic early warning systems for EU14 based on the 2008 crisis: proposed estimation and model assessment for classification forecasting," Journal of Banking Regulation, Palgrave Macmillan, vol. 20(3), pages 226-244, September.
    19. Parrado-Martínez, Purificación & Gómez-Fernández-Aguado, Pilar & Partal-Ureña, Antonio, 2019. "Factors influencing the European bank’s probability of default: An application of SYMBOL methodology," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 61(C), pages 223-240.
    20. Papanikolaou, Nikolaos I., 2018. "To be bailed out or to be left to fail? A dynamic competing risks hazard analysis," Journal of Financial Stability, Elsevier, vol. 34(C), pages 61-85.
    21. Buckmann, Marcus & Gallego Marquez, Paula & Gimpelewicz, Mariana & Kapadia, Sujit & Rismanchi, Katie, 2023. "The more the merrier? Evidence on the value of multiple requirements in bank regulation," Journal of Banking & Finance, Elsevier, vol. 149(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
    • G38 - Financial Economics - - Corporate Finance and Governance - - - Government Policy and Regulation

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reveco:v:98:y:2025:i:c:s1059056025001145. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620165 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.