Multi-expert operational risk management

Operational risk management is the process of monitoring, evaluating, and changing courses of actions with potential detrimental consequences in real time. In this paper, we extend the decision models proposed in the Literature for individual risk managers to account for situations, where multiple risk managers are involved. For this purpose, two dynamic and adaptive preference aggregation models for cardinal and ordinal assessments are proposed and discussed. The mechanical aspects of the models are then validated using field data collected from experienced operational risk managers in an individual-expert setting. Sensitivity analysis indicates that the models have enough flexibility to be adapted to account for behavioral considerations. The paper closes with a research agenda.