The “Whys” and “Hows” of Operational Risk Model Benchmarking

Samantha C Roberts

Operational risk, the newest of the risk disciplines, made the regulatory big time in the US in 2007 with the publication of “Risk-based Capital Standards: Advanced Capital Adequacy Framework – Basel II” (the advanced approaches rule). The rule required qualifying core banks and permitted other qualifying banks to use advanced measurement approaches (AMA) to calculate risk-based capital requirements for operational risk. At the time of publication, financial regulators anticipated that the operational risk discipline would mature and converge toward a relatively narrow range of risk modelling and management practices. By and large, this maturation remains elusive, especially for quantitative operational risk modelling.

The discipline is seemingly destined to reflect the same level of idiosyncrasy as the risks it measures. Operational risks vary within and across institutions, by financial activity, organisational structure and geographic jurisdictions, and the result is that no one model or measurement approach works for every risk type, purpose or institution. A typical AMA bank has a portfolio of models that rely upon different data sources (internal, scenario analysis output