Statistical models for operational risk management

Chiara Cornalba and Paolo Giudici

Physica A: Statistical Mechanics and its Applications, 2004, vol. 338, issue 1, 166-172

Abstract: The Basel Committee on Banking Supervision has released, in the last few years, recommendations for the correct determination of the risks to which a banking organization is subject. This concerns, in particular, operational risks, which are all those management events that may determine unexpected losses. It is necessary to develop valid statistical models to measure and, consequently, predict, such operational risks. In the paper we present the possible approaches, including our own proposal, which is based on Bayesian networks.

Keywords: Bayesian networks; Operational risk management; Predictive models; Value at risk (search for similar items in EconPapers)
Date: 2004
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Citations: View citations in EconPapers (18)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:338:y:2004:i:1:p:166-172

DOI: 10.1016/j.physa.2004.02.039

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