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A Bayesian Networks Approach to Operational Risk

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  • V. Aquaro
  • M. Bardoscia
  • R. Bellotti
  • A. Consiglio
  • F. De Carlo
  • G. Ferri

Abstract

A system for Operational Risk management based on the computational paradigm of Bayesian Networks is presented. The algorithm allows the construction of a Bayesian Network targeted for each bank using only internal loss data, and takes into account in a simple and realistic way the correlations among different processes of the bank. The internal losses are averaged over a variable time horizon, so that the correlations at different times are removed, while the correlations at the same time are kept: the averaged losses are thus suitable to perform the learning of the network topology and parameters. The algorithm has been validated on synthetic time series. It should be stressed that the practical implementation of the proposed algorithm has a small impact on the organizational structure of a bank and requires an investment in human resources limited to the computational area.

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File URL: http://arxiv.org/pdf/0906.3968
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Paper provided by arXiv.org in its series Papers with number 0906.3968.

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Date of creation: Jun 2009
Date of revision: Feb 2012
Publication status: Published in Physica A 389 (2010), pp. 1721-1728
Handle: RePEc:arx:papers:0906.3968

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Web page: http://arxiv.org/

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Cited by:
  1. Wang, Zongrun & Wang, Wuchao & Chen, Xiaohong & Jin, Yanbo & Zhou, Yanju, 2012. "Using BS-PSD-LDA approach to measure operational risk of Chinese commercial banks," Economic Modelling, Elsevier, vol. 29(6), pages 2095-2103.

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