The Basel Committee on Banking Supervision has released, in the last few years, recommen- dations 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.
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Titolo: | Statistical models for operational risk management |
Autori: | |
Data di pubblicazione: | 2004 |
Rivista: | |
Abstract: | The Basel Committee on Banking Supervision has released, in the last few years, recommen- dations 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. |
Handle: | http://hdl.handle.net/11571/106144 |
Appare nelle tipologie: | 1.1 Articolo in rivista |