Operational risk scenario documentation permits creating as many user defined data capture fields and tabs as needed to document the different aspects of the operational risk scenario: mappings to KRIs, RCSAs, Processes, etc.; include support data (internal or external); controls; mitigation alternatives; or else.

Operational risk scenario evaluation is also user defined and can take as many points in the distribution curve as needed (i.e., worst loss in 7 years, worst possible loss, typical loss or any other). Multiple experts can answer the same operational risk scenario evaluation and their answers will be automatically aggregated into a consolidated asnwer based on each expert precision for a more robust answer.

Robustness of calculation is increased by evaluating the sensitivity of operational risk scenario results and correlations versus their inputs. Sensitivity tests are frequently requested by validators and supervisors to proof the exhaustive and robust validation of the operational risk scenario results.

Scenarium.OR automatically performs the sensitivity shocks on operational risk scenario evaluations and aggregation correlations and provides the results of the shocks into the capital automatically.

Scenarium.OR enables Analytics to the first line of defence to evaluate the risk profile and the impact of mitigation, using an on-the-fly Monte Carlo simulation feature. This helps to change the internal culture of the institution towards a more scientific risk evaluation and robust risk mitigation decisioning.

The mitigation plan Net Present Value (NPV) can be calculated in order to build the business case for justifying implementation and required investments. The differences in the risk profile of before and after mitigation together with the implementation cost of the control permits to determine whether the action plan add or not net present value to the institution.

Scenarium.OR also permits to analyse the impact of insurance programs into the risk profile from the scenario. The different insurance policy conditions (deductible, maximum coverage, maximum number of events and other) are configured and their impact into the loss distribution analysed. Similarly to the mitigation plan, the insurance optimization permits to evaluate the NPV of the insurance cost by evaluating the capital and expected loss savings versus the cost of the insurance.

The insurance optimization permits to evaluate the actual protection offered by the insurer and the means to negotiate changes in the policy conditions and coverages.

Operational risk operational risk scenarios can be modelled with unlimited number of probability distributions and fit to quantiles and distribution moments and Scenarium.OR provides multiple means for the evaluation of the goodness of fit.

For more detailed modelling, Scenarium.OR also permits to model operational risk scenarios using Bayesian networks and their simulation output be integrated with the rest of the standard scenarios. Scenarium.OR also permits to determine the mitigation plan NPV as in the normal modelling.

Scenarium.OR provides a robust framework for calculating operational risk scenario correlations using a sensitivity to common risk drivers approach. This approach allows a transparent and solidly supported calculation of operational risk correlations.

Correlations and scenarios and then fed into a Monte Carlo simulation for determining capital requirements and generating economic value add metrics to manage operational risks.

Institutions may use a large number of operational risk scenarios to compute operational risk capital (i.e. 3,000 or more scenarios). These operational risk scenarios usually belong to different business lines, risk types, legal entities or even countries. Such large number of operational risk scenarios can be aggregated in several steps using successive copulas. This process of aggregation in multiple steps permits to obtain stand-alone capital charges for sub-organizational entities such as legal entities, business lines, national entities, regional entities as well as the global capital requirement for the consolidated entity.