Using Bayesian Networks to model Expected and Unexpected Operational Losses

This report describes the use of Bayesian Networks (BNs) to model statistical loss distributions in financial operational risk scenarios. Its’ focus is on modelling “thick” tail, or unexpected, loss events using mixtures of appropriate loss frequency and severity distributions where these mixtures are conditioned on causal variables that model the capability or effectiveness of the underlying controls process. We conclude that BNs can help combine qualitative data from experts and quantitative data from historical loss databases in a principled way and as such they go some way to meeting the requirements of the draft Basel II Accord, [Basel 2001], for an Advanced Measurement Approach (AMA). The AgenaRisk software was used to create the example analysis contained herein.