The operational risk tree methodology for managing operational risk exposure and measuring capital requirements

Monte Carlo simulation is applied to measuring operational risk via a modified decision tree. The author describes a simulation based approach to measuring economic and regulatory capital for operational risk. Except in relatively rare cases where sufficient data exists, quantitative operational risk has grown to depend upon expert opinion via scenario analysis to fill in the missing data. The author explains the limitations and shortcomings of the current approach and details an alternative approach using a modified decision tree to address many of these shortcomings. While in the absence of data we still depend upon expert opinion, there is good reason to believe that the method of collecting this opinion can have great impact upon the confidence in, and reproducibility of, the results.