Implications of Alternative Operational Risk Modeling Techniques

45 Pages Posted: 20 Jun 2004

See all articles by Patrick de Fontnouvelle

Patrick de Fontnouvelle

Federal Reserve Bank of Boston - Supervision and Regulation

Eric S. Rosengren

Federal Reserve Bank of Boston - Supervision and Regulation

John S. Jordan

FitchRisk

Multiple version iconThere are 2 versions of this paper

Date Written: June 2004

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.

Suggested Citation

de Fontnouvelle, Patrick and Rosengren, Eric S. and Jordan, John S., Implications of Alternative Operational Risk Modeling Techniques (June 2004). Available at SSRN: https://ssrn.com/abstract=556823 or http://dx.doi.org/10.2139/ssrn.556823

Patrick De Fontnouvelle (Contact Author)

Federal Reserve Bank of Boston - Supervision and Regulation ( email )

600 Atlantic Avenue
P.O. Box 2076
Boston, MA 02210
United States
617-973-3659 (Phone)
617-973-3219 (Fax)

Eric S. Rosengren

Federal Reserve Bank of Boston - Supervision and Regulation ( email )

600 Atlantic Avenue
P.O. Box 2076
Boston, MA 02210
United States
617-973-3090 (Phone)
617-973-3219 (Fax)

John S. Jordan

FitchRisk ( email )

17 State Street
New York, NY 10004
United States

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