IDEAS home Printed from https://ideas.repec.org/a/col/000129/015179.html
   My bibliography  Save this article

An analysis on operational risk in international banking: A Bayesian approach (2007–2011)

Author

Listed:
  • Francisco Venegas-Martínez
  • José Francisco Martínez-Sánchez
  • María Teresa V. Martínez-Palacios

Abstract

This study aims to develop a Bayesian methodology to identify, quantify and measure operational risk in several business lines of commercial banking. To do this, a Bayesian network (BN) model is designed with prior and subsequent distributions to estimate the frequency and severity. Regarding the subsequent distributions, an inference procedure for the maximum expected loss, for a period of 20 days, is carried out by using the Monte Carlo simulation method. The business lines analyzed are marketing and sales, retail banking and private banking, which all together accounted for 88.5% of the losses in 2011. Data was obtained for the period 2007–2011 from the Riskdata Operational Exchange Association (ORX), and external data was provided from qualified experts to complete the missing records or to improve its poor quality.

Suggested Citation

  • Francisco Venegas-Martínez & José Francisco Martínez-Sánchez & María Teresa V. Martínez-Palacios, 2016. "An analysis on operational risk in international banking: A Bayesian approach (2007–2011)," Estudios Gerenciales, Universidad Icesi, vol. 32(140), pages 208-220, September.
    • Handle: RePEc:col:000129:015179
    as

    Download full text from publisher

    File URL: http://www.icesi.edu.co/revistas/index.php/estudios_gerenciales/article/view/2299
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Aquaro, V. & Bardoscia, M. & Bellotti, R. & Consiglio, A. & De Carlo, F. & Ferri, G., 2010. "A Bayesian Networks approach to Operational Risk," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(8), pages 1721-1728.
    2. Degen, Matthias & Embrechts, Paul & Lambrigger, Dominik D., 2007. "The Quantitative Modeling of Operational Risk: Between G-and-H and EVT," ASTIN Bulletin, Cambridge University Press, vol. 37(2), pages 265-291, November.
    3. Gregor Heinrich, 2006. "Riesgo operacional, pagos, sistemas de pago y aplicación de Basilea II en América Latina: evolución más reciente," Boletín, CEMLA, vol. 0(4), pages 191-204, Octubre-d.
    4. Philippe Artzner & Freddy Delbaen & Jean‐Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228, July.
    5. 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.
    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. Sophia Beckett Velez, 2021. "Idiosyncratic Viral Loss Theory: Systemic Operational Losses in Banks," JRFM, MDPI, vol. 14(2), pages 1-13, February.
    2. José Ruiz-Canela López, 2021. "How Can Enterprise Risk Management Help in Evaluating the Operational Risks for a Telecommunications Company?," JRFM, MDPI, vol. 14(3), pages 1-26, March.

    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. Embrechts, Paul & Neslehová, Johanna & Wüthrich, Mario V., 2009. "Additivity properties for Value-at-Risk under Archimedean dependence and heavy-tailedness," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 164-169, April.
    2. José Francisco Martínez-Sánchez & Francisco Venegas-Martínez, 2013. "Riesgo operacional en la banca trasnacional: un enfoque bayesiano," Ensayos Revista de Economia, Universidad Autonoma de Nuevo Leon, Facultad de Economia, vol. 0(1), pages 31-72, May.
    3. Pavel V. Shevchenko, 2010. "Implementing loss distribution approach for operational risk," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 26(3), pages 277-307, May.
    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. Dominik D. Lambrigger & Pavel V. Shevchenko & Mario V. Wuthrich, 2009. "The Quantification of Operational Risk using Internal Data, Relevant External Data and Expert Opinions," Papers 0904.1361, arXiv.org.
    6. J. Christopher Westland, 2015. "Economics of eBay’s buyer protection plan," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 1(1), pages 1-20, December.
    7. Steven Kou & Xianhua Peng, 2016. "On the Measurement of Economic Tail Risk," Operations Research, INFORMS, vol. 64(5), pages 1056-1072, October.
    8. 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.
    9. Pflug Georg Ch. & Schaller Peter, 2009. "A note on pivotal Value-at-Risk estimates," Statistics & Risk Modeling, De Gruyter, vol. 27(3), pages 201-209, December.
    10. Pavel V. Shevchenko, 2009. "Implementing Loss Distribution Approach for Operational Risk," Papers 0904.1805, arXiv.org, revised Jul 2009.
    11. Yuyu Chen & Taizhong Hu & Ruodu Wang & Zhenfeng Zou, 2024. "Dominance between combinations of infinite-mean Pareto random variables," Papers 2404.18467, arXiv.org.
    12. Dominique Guegan & Bertrand Hassani & Cédric Naud, 2010. "An efficient threshold choice for operational risk capital computation," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00544342, HAL.
    13. Joan del castillo & Jalila Daoudi & Isabel Serra, 2012. "The full-tails gamma distribution applied to model extreme values," Papers 1211.0130, arXiv.org.
    14. Steven Kou & Xianhua Peng, 2014. "On the Measurement of Economic Tail Risk," Papers 1401.4787, arXiv.org, revised Aug 2015.
    15. Julia S. Mehlitz & Benjamin R. Auer, 2021. "Time‐varying dynamics of expected shortfall in commodity futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(6), pages 895-925, June.
    16. Gareth W. Peters & Rodrigo S. Targino & Pavel V. Shevchenko, 2013. "Understanding Operational Risk Capital Approximations: First and Second Orders," Papers 1303.2910, arXiv.org.
    17. Mao, Tiantian & Lv, Wenhua & Hu, Taizhong, 2012. "Second-order expansions of the risk concentration based on CTE," Insurance: Mathematics and Economics, Elsevier, vol. 51(2), pages 449-456.
    18. Yuyu Chen & Paul Embrechts & Ruodu Wang, 2022. "An unexpected stochastic dominance: Pareto distributions, dependence, and diversification," Papers 2208.08471, arXiv.org, revised Mar 2024.
    19. Degen, Matthias & Lambrigger, Dominik D. & Segers, Johan, 2010. "Risk concentration and diversification: Second-order properties," Insurance: Mathematics and Economics, Elsevier, vol. 46(3), pages 541-546, June.
    20. Mora Valencia Andrés, 2014. "El uso de la distribución g-h en riesgo operativo," Contaduría y Administración, Accounting and Management, vol. 59(1), pages 123-148, enero-mar.

    More about this item

    Keywords

    Operational risk; Bayesian analysis; Monte Carlo simulation;
    All these keywords.

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

    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:col:000129:015179. 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: Coordinador ICESI (email available below). General contact details of provider: https://edirc.repec.org/data/fciceco.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.