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Credal Networks for Operational Risk Measurement and Management
 

Summary: Credal Networks for Operational Risk
Measurement and Management
Alessandro Antonucci, Alberto Piatti, and Marco Zaffalon
Istituto "Dalle Molle" di Studi sull'Intelligenza Artificiale
Via Cantonale, Galleria 2, CH-6928 Manno, Switzerland
{alessandro,alberto.piatti,zaffalon}@idsia.ch
Abstract. According to widely accepted guidelines for self-regulation,
the capital requirements of a bank should relate to the level of risk with
respect to three different categories. Among them, operational risk is
the more difficult to assess, as it requires merging expert judgments and
quantitative information about the functional structure of the bank. A
number of approaches to the evaluation of operational risk based on
Bayesian networks have been recently considered. In this paper, we pro-
pose credal networks, which are a generalization of Bayesian networks to
imprecise probabilities, as a more appropriate framework for the mea-
surement and management of operational risk. The reason is the higher
flexibility provided by credal networks compared to Bayesian networks in
the quantification of the probabilities underlying the model: this makes it
possible to represent human expertise required for these evaluations in a
credible and robust way. We use a real-world application to demonstrate

  

Source: Antonucci, Alessandro - Istituto Dalle Molle di Studi sull'Intelligenza Artificiale (IDSIA)
Zaffalon, Marco - Istituto Dalle Molle di Studi sull' Intelligenza Artificiale (IDSIA)

 

Collections: Computer Technologies and Information Sciences