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Quantitative modeling of operational risk losses when combining internal and external data

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Abstract

We present an overview of methods to estimate risk arising from operational losses. Our approach is based on the study of the statistical severity distribution of a single loss. We analyze the fundamental issues that arise in practice when modeling operational risk data. We address the statistical problem of estimating an operational risk distribution, both in standard abundant data situations and when our available data is challenged from the inclusion of external data or because of underreporting. Our presentation includes an application to show that failure to account for underreporting may lead to a substantial underestimation of operational risk measures. The use of external data information can easily be incorporated in our modeling approach.

Suggested Citation

  • Nielsen, Jens Perch & Guillen, Montserrat & Bolance, Catalina & Gustafsson, Jim, 2012. "Quantitative modeling of operational risk losses when combining internal and external data," Journal of Financial Transformation, Capco Institute, vol. 35, pages 179-185.
    • Handle: RePEc:ris:jofitr:1538
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    More about this item

    Keywords

    operational risk; quantitative modeling; operational loss; risk modeling;
    All these keywords.

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
    • 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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