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Implications of Alternative Operational Risk Modeling Techniques

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Author Info
Patrick de Fontnouvelle
John Jordan
Eric Rosengren

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Abstract

Quantification of operational risk has received increased attention with the inclusion of an explicit capital charge for operational risk under the new Basle proposal. The proposal provides significant flexibility for banks to use internal models to estimate their operational risk, and the associated capital needed for unexpected losses. Most banks have used variants of value at risk models that estimate frequency, severity, and loss distributions. This paper examines the empirical regularities in operational loss data. Using loss data from six large internationally active banking institutions, we find that loss data by event types are quite similar across institutions. Furthermore, our results are consistent with economic capital numbers disclosed by some large banks, and also with the results of studies modeling losses using publicly available "external" loss data.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 11103.

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Date of creation: Feb 2005
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Handle: RePEc:nbr:nberwo:11103

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G2 - Financial Economics - - Financial Institutions and Services

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References listed on IDEAS
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  1. Huisman, Ronald, et al, 2001. "Tail-Index Estimates in Small Samples," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(2), pages 208-16, April.
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  1. Andreas Jobst, 2007. "Operational Risk--The Sting is Still in the Tail but the Poison Depends on the Dose," IMF Working Papers 07/239, International Monetary Fund. [Downloadable!]
  2. Barbu Teodora Cristina & Olteanu (Puiu) Ana Cornelia & Radu Alina Nicoleta, 2008. "The necessity of operational risk management and quantification," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 3(1), pages 661-667, May. [Downloadable!]
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