IDEAS home Printed from https://ideas.repec.org/p/ulb/ulbeco/2013-14158.html
   My bibliography  Save this paper

Practical methods for measuring and managing operational risk in the financial sector: a clinical study

Author

Listed:
  • Georges Hübner
  • Jean-Philippe Peters

Abstract

This paper analyzes the implications of the advanced measurement approach (AMA) for the assessment of operational risk. Through a clinical case study on a matrix of two selected business lines and two event types of a large financial institution, we develop a procedure that addresses the major issues faced by banks in the implementation of the AMA. For each cell, we calibrate two truncated distributions functions, one for "normal" losses and the other for the "extreme" losses. In addition, we propose a method to include external data in the framework. We then estimate the impact of operational risk management on bank profitability, through an adapted measure of RAROC. The results suggest that substantial savings can be achieved through active management techniques. © 2007 Elsevier B.V. All rights reserved.

Suggested Citation

  • Georges Hübner & Jean-Philippe Peters, 2008. "Practical methods for measuring and managing operational risk in the financial sector: a clinical study," ULB Institutional Repository 2013/14158, ULB -- Universite Libre de Bruxelles.
    • Handle: RePEc:ulb:ulbeco:2013/14158
    Note: SCOPUS: ar.j
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    Other versions of this item:

    References listed on IDEAS

    as
    1. François Longin & Bruno Solnik, 2001. "Extreme Correlation of International Equity Markets," Journal of Finance, American Finance Association, vol. 56(2), pages 649-676, April.
    2. Patrick de Fontnouvelle & Eric Rosengren & John Jordan, 2007. "Implications of Alternative Operational Risk Modeling Techniques," NBER Chapters, in: The Risks of Financial Institutions, pages 475-505, National Bureau of Economic Research, Inc.
    3. Marco Moscadelli, 2004. "The modelling of operational risk: experience with the analysis of the data collected by the Basel Committee," Temi di discussione (Economic working papers) 517, Bank of Italy, Economic Research and International Relations Area.
    4. Chavez-Demoulin, V. & Embrechts, P. & Neslehova, J., 2006. "Quantitative models for operational risk: Extremes, dependence and aggregation," Journal of Banking & Finance, Elsevier, vol. 30(10), pages 2635-2658, October.
    5. Frachot, Antoine & Roncalli, Thierry & Salomon, Eric, 2004. "The Correlation Problem in Operational Risk," MPRA Paper 38052, University Library of Munich, Germany.
    6. Drees, Holger & Kaufmann, Edgar, 1998. "Selecting the optimal sample fraction in univariate extreme value estimation," Stochastic Processes and their Applications, Elsevier, vol. 75(2), pages 149-172, July.
    7. Hurlimann, Werner, 2004. "Fitting bivariate cumulative returns with copulas," Computational Statistics & Data Analysis, Elsevier, vol. 45(2), pages 355-372, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Stefan Mittnik & Sandra Paterlini & Tina Yener, 2011. "Operational–risk Dependencies and the Determination of Risk Capital," Center for Economic Research (RECent) 070, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
    2. Yuqian Xu & Lingjiong Zhu & Michael Pinedo, 2020. "Operational Risk Management: A Stochastic Control Framework with Preventive and Corrective Controls," Operations Research, INFORMS, vol. 68(6), pages 1804-1825, November.
    3. Yinhong Yao & Jianping Li, 2022. "Operational risk assessment of third-party payment platforms: a case study of China," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-20, December.
    4. Marco Rocco, 2011. "Extreme value theory for finance: a survey," Questioni di Economia e Finanza (Occasional Papers) 99, Bank of Italy, Economic Research and International Relations Area.
    5. Chang, Carolyn W. & Chang, Jack S.K. & Lu, WeLi, 2010. "Pricing catastrophe options with stochastic claim arrival intensity in claim time," Journal of Banking & Finance, Elsevier, vol. 34(1), pages 24-32, January.
    6. Eling, Martin & Loperfido, Nicola, 2017. "Data breaches: Goodness of fit, pricing, and risk measurement," Insurance: Mathematics and Economics, Elsevier, vol. 75(C), pages 126-136.
    7. Georges Dionne & Samir Saissi Hassani, . "Hidden Markov regimes in operational loss data: application to the recent financial crisis," Journal of Operational Risk, Journal of Operational Risk.
    8. Xiaoqian Zhu & Jianping Li & Dengsheng Wu, 2019. "Should the Advanced Measurement Approach for Operational Risk be Discarded? Evidence from the Chinese Banking Industry," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 22(01), pages 1-15, March.
    9. Dahen, Hela & Dionne, Georges, 2010. "Scaling models for the severity and frequency of external operational loss data," Journal of Banking & Finance, Elsevier, vol. 34(7), pages 1484-1496, July.
    10. Hela Dahen & Georges Dionne & Daniel Zajdenweber, 2010. "Extremal Events in a Bank Operational Losses," Cahiers de recherche 1014, CIRPEE.
    11. Groll, Andreas & Hambuckers, Julien & Kneib, Thomas & Umlauf, Nikolaus, 2019. "LASSO-type penalization in the framework of generalized additive models for location, scale and shape," Computational Statistics & Data Analysis, Elsevier, vol. 140(C), pages 59-73.
    12. Tyrone Lin & Chia-Chi Lee & Yu-Chuan Kuan, 2013. "The optimal operational risk capital requirement by applying the advanced measurement approach," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 21(1), pages 85-101, January.
    13. Wang, Zongrun & Wang, Wuchao & Chen, Xiaohong & Jin, Yanbo & Zhou, Yanju, 2012. "Using BS-PSD-LDA approach to measure operational risk of Chinese commercial banks," Economic Modelling, Elsevier, vol. 29(6), pages 2095-2103.
    14. Lu, Zhaoyang, 2011. "Modeling the yearly Value-at-Risk for operational risk in Chinese commercial banks," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 82(4), pages 604-616.
    15. Lu Wei & Jianping Li & Xiaoqian Zhu, 2018. "Operational Loss Data Collection: A Literature Review," Annals of Data Science, Springer, vol. 5(3), pages 313-337, September.
    16. Ongena, Steven & Conlon, Thomas & Huan, Xing, 2020. "Operational Risk Capital," CEPR Discussion Papers 15096, C.E.P.R. Discussion Papers.
    17. Guasti Lima Fabiano & Castro Junior Sant Clair de & Pimenta Júnior Tabajara & Gaio Luiz Eduardo, 2014. "Performance of the different RAROC models and their relation with the creation of economic value: A study of the largest banks operating in Brazil," Contaduría y Administración, Accounting and Management, vol. 59(4), pages 87-104, octubre-d.
    18. Feria-Domínguez, José Manuel & Jiménez-Rodríguez, Enrique & Sholarin, Ola, 2015. "Tackling the over-dispersion of operational risk: Implications on capital adequacy requirements," The North American Journal of Economics and Finance, Elsevier, vol. 31(C), pages 206-221.
    19. Ming-Tao CHUNG & Ming-Hua HSIEH & Yan-Ping CHI, 2017. "Computation of Operational Risk for Financial Institutions," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 77-87, September.
    20. Ajjima Jiravichai & Ruth Banomyong, 2022. "A Proposed Methodology for Literature Review on Operational Risk Management in Banks," Risks, MDPI, vol. 10(5), pages 1-18, May.
    21. Brechmann, Eike & Czado, Claudia & Paterlini, Sandra, 2014. "Flexible dependence modeling of operational risk losses and its impact on total capital requirements," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 271-285.
    22. Elshahat, A. & Parhizgari, Ali & Hong, Liang, 2012. "The information content of the Banking Regulatory Agencies and the Depository Credit Intermediation Institutions," Journal of Economics and Business, Elsevier, vol. 64(1), pages 90-104.
    23. Uddin, Md Hamid & Mollah, Sabur & Islam, Nazrul & Ali, Md Hakim, 2023. "Does digital transformation matter for operational risk exposure?," Technological Forecasting and Social Change, Elsevier, vol. 197(C).

    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. Lu, Zhaoyang, 2011. "Modeling the yearly Value-at-Risk for operational risk in Chinese commercial banks," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 82(4), pages 604-616.
    2. Tursunalieva, Ainura & Silvapulle, Param, 2016. "Nonparametric estimation of operational value-at-risk (OpVaR)," Insurance: Mathematics and Economics, Elsevier, vol. 69(C), pages 194-201.
    3. Albrecht, Peter & Schwake, Edmund & Winter, Peter, 2007. "Quantifizierung operationeller Risiken: Der Loss Distribution Approach," German Risk and Insurance Review (GRIR), University of Cologne, Department of Risk Management and Insurance, vol. 3(1), pages 1-45.
    4. Udo Milkau & Jürgen Bott, 2018. "Active Management of Operational Risk in the Regimes of the “Unknown”: What Can Machine Learning or Heuristics Deliver?," Risks, MDPI, vol. 6(2), pages 1-16, April.
    5. Stefan Mittnik & Sandra Paterlini & Tina Yener, 2011. "Operational–risk Dependencies and the Determination of Risk Capital," Center for Economic Research (RECent) 070, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
    6. Marco Rocco, 2011. "Extreme value theory for finance: a survey," Questioni di Economia e Finanza (Occasional Papers) 99, Bank of Italy, Economic Research and International Relations Area.
    7. Robert Jarrow & Jeff Oxman & Yildiray Yildirim, 2010. "The cost of operational risk loss insurance," Review of Derivatives Research, Springer, vol. 13(3), pages 273-295, October.
    8. Eckert, Christian & Gatzert, Nadine, 2017. "Modeling operational risk incorporating reputation risk: An integrated analysis for financial firms," Insurance: Mathematics and Economics, Elsevier, vol. 72(C), pages 122-137.
    9. Alina Mihaela Dima, 2009. "Operational Risk Assesement Tools for Quality Management in Banking Services," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 11(26), pages 364-372, June.
    10. Robert Jarrow, 2017. "Operational Risk," World Scientific Book Chapters, in: THE ECONOMIC FOUNDATIONS OF RISK MANAGEMENT Theory, Practice, and Applications, chapter 8, pages 69-70, World Scientific Publishing Co. Pte. Ltd..
    11. Anna Chernobai and Svetlozar T. Rachev, . "Applying robust methods to operational risk modeling," Journal of Operational Risk, Journal of Operational Risk.
    12. S�verine Plunus & Georges Hübner & Jean-Philippe Peters, 2012. "Measuring operational risk in financial institutions," Applied Financial Economics, Taylor & Francis Journals, vol. 22(18), pages 1553-1569, September.
    13. Brechmann, Eike & Czado, Claudia & Paterlini, Sandra, 2014. "Flexible dependence modeling of operational risk losses and its impact on total capital requirements," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 271-285.
    14. Roch, Oriol & Alegre, Antonio, 2006. "Testing the bivariate distribution of daily equity returns using copulas. An application to the Spanish stock market," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1312-1329, November.
    15. Kley, Oliver & Klüppelberg, Claudia & Paterlini, Sandra, 2020. "Modelling extremal dependence for operational risk by a bipartite graph," Journal of Banking & Finance, Elsevier, vol. 117(C).
    16. Di Lascio, F. Marta L. & Giammusso, Davide & Puccetti, Giovanni, 2018. "A clustering approach and a rule of thumb for risk aggregation," Journal of Banking & Finance, Elsevier, vol. 96(C), pages 236-248.
    17. Chavez-Demoulin, V. & Embrechts, P. & Neslehova, J., 2006. "Quantitative models for operational risk: Extremes, dependence and aggregation," Journal of Banking & Finance, Elsevier, vol. 30(10), pages 2635-2658, October.
    18. Xiaolin Luo & Pavel V. Shevchenko & John B. Donnelly, 2009. "Addressing the Impact of Data Truncation and Parameter Uncertainty on Operational Risk Estimates," Papers 0904.2910, arXiv.org.
    19. Pavel V. Shevchenko, 2009. "Implementing Loss Distribution Approach for Operational Risk," Papers 0904.1805, arXiv.org, revised Jul 2009.
    20. Hans Buhlmann & Pavel V. Shevchenko & Mario V. Wuthrich, 2009. "A "Toy" Model for Operational Risk Quantification using Credibility Theory," Papers 0904.1772, arXiv.org.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:ulb:ulbeco:2013/14158. 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: Benoit Pauwels (email available below). General contact details of provider: https://edirc.repec.org/data/ecsulbe.html .

    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.