The Quantification of Operational Risk using Internal Data, Relevant External Data and Expert Opinions

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dc.creatorLambrigger, Dominik D.
dc.creatorShevchenko, Pavel V.
dc.creatorWüthrich, Mario V.
dc.date2009-04-08
dc.date.accessioned2026-07-07T13:01:44Z
dc.date.available2026-07-07T13:01:44Z
dc.descriptionTo quantify an operational risk capital charge under Basel II, many banks adopt a Loss Distribution Approach. Under this approach, quantification of the frequency and severity distributions of operational risk involves the bank's internal data, expert opinions and relevant external data. In this paper we suggest a new approach, based on a Bayesian inference method, that allows for a combination of these three sources of information to estimate the parameters of the risk frequency and severity distributions.
dc.identifierhttps://arxiv.org/abs/0904.1361
dc.identifierhttp://arxiv.org/abs/0904.1361
dc.identifierThe Journal of Operational Risk 2(3), pp.3-27, 2007. www.journalofoperationalrisk.com
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/226246
dc.subjectRisk Management
dc.subjectStatistical Finance
dc.titleThe Quantification of Operational Risk using Internal Data, Relevant External Data and Expert Opinions
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