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Operational Risk - Scenario Analysis

Author

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  • Milan Rippel
  • Petr Teplý

Abstract

This paper focuses on operational risk measurement techniques and on economic capital estimation methods. A data sample of operational losses provided by an anonymous Central European bank is analyzed using several approaches. Multiple statistical concepts such as the Loss Distribution Approach and the Extreme Value Theory, including scenario analysis method, are considered. Custom plausible loss events defined in a particular scenario are merged with the original data sample and their impact on capital estimates and on the financial institution as a whole is evaluated. Two main questions are assessed - what is the most appropriate statistical method to measure and model operational loss data distribution and what is the impact of hypothetical plausible events on the financial institution. The g&h distribution was evaluated to be the most suitable one for operational risk modeling. The method based on the combination of historical loss events modeling and scenario analysis provides reasonable capital estimates and allows for the measurement of the impact of very extreme events on banking operations.

Suggested Citation

  • Milan Rippel & Petr Teplý, 2011. "Operational Risk - Scenario Analysis," Prague Economic Papers, Prague University of Economics and Business, vol. 2011(1), pages 23-39.
    • Handle: RePEc:prg:jnlpep:v:2011:y:2011:i:1:id:385:p:23-39
    DOI: 10.18267/j.pep.385
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    References listed on IDEAS

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    1. Radovan Chalupka & Petr Teply, 2008. "Operational Risk Management and Implications for Bank’s Economic Capital – a Case Study," Working Papers IES 2008/17, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Sep 2008.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Häger, David & Andersen, Lasse B., 2010. "A knowledge based approach to loss severity assessment in financial institutions using Bayesian networks and loss determinants," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1635-1644, December.
    2. Tomáš Klinger & Petr Teplý, 2014. "Systemic Risk of the Global Banking System - An Agent-Based Network Model Approach," Prague Economic Papers, Prague University of Economics and Business, vol. 2014(1), pages 24-41.
    3. 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.
    4. Petr Teply & Libena Cernohorska & Jan Cernohorsky, 2010. "Key Economic Policy Lessons From The 2008 Financial Crisis," Anadolu University Journal of Social Sciences, Anadolu University, vol. 10(2), pages 123-134, May.
    5. Barbora Šútorová & Petr Teplý, 2014. "The Level of Capital and the Value of EU Banks under Basel III," Prague Economic Papers, Prague University of Economics and Business, vol. 2014(2), pages 143-161.
    6. Daniel Stavárek & Iveta Řepková, 2012. "Efficiency in the Czech banking industry: A non-parametric approach," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 60(2), pages 357-366.
    7. Milan Rippel & Lucie Suchánková & Petr Teplý, 2012. "Pojištění jako nástroj řízení operačního rizika - případová studie [The Role of Insurance in Operational Risk Mitigation - A Case Study]," Politická ekonomie, Prague University of Economics and Business, vol. 2012(4), pages 523-535.

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    1. Petr Teply & Libena Cernohorska & Jan Cernohorsky, 2010. "Key Economic Policy Lessons From The 2008 Financial Crisis," Anadolu University Journal of Social Sciences, Anadolu University, vol. 10(2), pages 123-134, May.

    More about this item

    Keywords

    stress testing; operational risk; scenario analysis; economic capital; loss distribution approach; extreme value theory;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • 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

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