A Bayesian network structure for operational risk modelling in structured finance operations

Sanford, A and Moosa, I 2012, 'A Bayesian network structure for operational risk modelling in structured finance operations', Journal of the Operational Research Society, vol. 63, no. 4, pp. 431-444.


Document type: Journal Article
Collection: Journal Articles

Title A Bayesian network structure for operational risk modelling in structured finance operations
Author(s) Sanford, A
Moosa, I
Year 2012
Journal name Journal of the Operational Research Society
Volume number 63
Issue number 4
Start page 431
End page 444
Total pages 14
Publisher Palgrave Macmillan
Abstract This paper is concerned with the design of a Bayesian network structure that is suitable for operational risk modelling. The model's structure is designed specifically from the perspective of a business unit operational risk manager whose role is to measure, record, predict, communicate, analyse and control operational risk within their unit. The problem domain modelled is a functioning structured finance operations unit within a major Australian bank. The network model design incorporates a number of existing human factor frameworks to account for human error and operational risk events within the domain. The design also supports a modular structure, allowing for the inclusion of many operational loss event types, making it adaptable to different operational risk environments.
Subject Banking, Finance and Investment not elsewhere classified
Keyword(s) Banking
Bayesian networks
operational risk
cognitive mapping
artificial intelligence
DOI - identifier 10.1057/jors.2011.7
Copyright notice © 2012 Operational Research Society Ltd. All rights reserved.
ISSN 0160-5682
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