Abstract
| Original language | English |
|---|---|
| Pages (from-to) | 431 - 444 |
| Number of pages | 14 |
| Journal | Journal of the Operational Research Society |
| Volume | 63 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 2012 |
Cite this
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A Bayesian network structure for operational risk modelling in structured finance operations. / Sanford, Andrew Darryl; Moosa, Imad Ahmed.
In: Journal of the Operational Research Society, Vol. 63, No. 4, 2012, p. 431 - 444.Research output: Contribution to journal › Article › Research › peer-review
TY - JOUR
T1 - A Bayesian network structure for operational risk modelling in structured finance operations
AU - Sanford, Andrew Darryl
AU - Moosa, Imad Ahmed
PY - 2012
Y1 - 2012
N2 - 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.
AB - 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.
U2 - 10.1057/jors.2011.7
DO - 10.1057/jors.2011.7
M3 - Article
VL - 63
SP - 431
EP - 444
JO - Journal of the Operational Research Society
JF - Journal of the Operational Research Society
SN - 0160-5682
IS - 4
ER -