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Operational Risk - Scenario Analysis

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Abstract

Operational risk management and measurement has been paid an increasing attention in last years. The main two reasons are the Basel II requirements that were to be complied with by all international active financial institutions by the end of 2006 and recent severe operational risk loss events. 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 or the Extreme Value Theory are considered. One of the methods used for operational risk management is a scenario analysis. Under this method, 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 problems are assessed in this paper – 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 because its results are consistent even while using a scenario analysis method. The method based on the combination of historical loss events modeling and scenario analysis provides reasonable capital estimates for the financial institution and allows to measure impact of very extreme events and also to mitigate operational risk exposure.

Suggested Citation

  • Milan Rippel & Petr Teply, 2008. "Operational Risk - Scenario Analysis," Working Papers IES 2008/15, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Sep 2008.
  • Handle: RePEc:fau:wpaper:wp2008_15
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    File URL: http://ies.fsv.cuni.cz/default/file/download/id/8910
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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.
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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. 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, University of Economics, Prague, vol. 2012(4), pages 523-535.
    3. Tomáš Klinger & Petr Teplý, 2014. "Systemic Risk of the Global Banking System - An Agent-Based Network Model Approach," Prague Economic Papers, University of Economics, Prague, vol. 2014(1), pages 24-41.

    More about this item

    Keywords

    operational risk; scenario analysis; economic capital; loss distribution approach; extreme value theory;

    JEL classification:

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

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