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

Andrew Darryl Sanford, Imad Ahmed Moosa

    Research output: Contribution to journalArticleResearchpeer-review

    18 Citations (Scopus)

    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.
    Original languageEnglish
    Pages (from-to)431 - 444
    Number of pages14
    JournalJournal of the Operational Research Society
    Volume63
    Issue number4
    DOIs
    Publication statusPublished - 2012

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