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2008•Research Online (University of Wollongong)Requires access

Operational risks in banks

John R. Evans, Robert S. Womersley, D. Wong, Greg A Woodbury

Open publisher page 2 citations

Abstract

Through empirical analysis of operational risk in a bank we derive a model to represent the distribution of losses, which we compare with more traditional models of operational risk. Our findings suggest that the generalised extreme value distribution provides a good fit to the annual loss distribution and that some conventional methods to model severity are inadequate because they neglect the extreme percentiles which are important in the type of analysis required under Basel II. Awarded a 2008 JASSA Merit award.

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What this paper is about

Through empirical analysis of operational risk in a bank we derive a model to represent the distribution of losses, which we compare with more traditional models of operational risk. Our findings suggest that the generalised extreme value distribution provides a good fit to the annual loss distribution and that some conventional methods to model severity are inadequate because they neglect the extreme percentiles which are important in the type of analysis required under Basel II. Awarded a 2008 JASSA Merit award.

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OpenAlex reports 2 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Through empirical analysis of operational risk in a bank we derive a model to represent the distribution of losses, which we compare with more traditional models of operational risk. Our findings suggest that the generalised extreme value distribution provides a good fit to the annual loss distribution and that some conventional methods to model severity are inadequate because they neglect the extreme percentiles which are important in the type of analysis required under Basel II. Awarded a 2008 JASSA Merit award.

Key concepts: Business, Operational risk, Risk analysis (engineering), Risk management, Finance

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