Why operational risk modelling creates inverse incentives

Operational risk modelling has become commonplace in large international banks and is gaining popularity in the insurance industry as well. This is partly due to financial regulation (Basel II, Solvency II). This article argues that operational risk modelling is fundamentally flawed, despite efforts to resolve the scarce data in the tail of the probability distributions. Potential solutions are special statistical techniques or shared (external) data initiatives. While capital regulation might be one perspective, internal capital modelling efforts are also flawed because of the main principles of the RAROC methodology. Rather than handling the issue of data scarcity, institutions and regulators should better focus on operational risk management and avoid large losses. Capital regulation for operational risk should be further simplified.