OpRisk Scenario Analysis, Operational Risk Scenario Analysis

Structure Scenario Analysis (SSA) is a best of breed web-based software for the management of operational risk using operational risk scenario analysis evaluation, modelling, quantification, economic capital calculation and mitigation. The modelling and quantification are designed to translate risk metrics into economic value metrics such as capital requirements, cost of risk and NPV of mitigation investments. This design permits to boost the buy-in from senior and upper management on the operational risk management program and maximises the influence of the operational risk function over the organization.
Structured Scenario Analysis is used by multiple leading international institutions (banks and insurance companies) in the determination of capital requirements for Basel`s Pillar 2 and ICAAP and Internal Models and ORSA under Solvency II. It has received 5 awards by Risk.Net and InsuranceERM including Best Scenario Software of the Year (2018 and 2019), Best Stress Scenario Software and Best Operational Risk Solution (contact The Analytics Boutique for a demo and commercial details).

In addition, our methods have been widely published and our publications recognised by top practitioners (see Actuary Magazine and RiskBook).

The benefits of Structured Scenario Analysis are as follows:

  • Boost the quality and robustness of operational risk scenario evaluations through different features for mitigating cognitive biases, sensitivity analysis in operational risk scenario answers and correlations, full traceability of results and more.
  • Maximize the efficiency of the operational risk scenario analysis process by eliminating manual processes and low value-added tasks: email invitations, automatic generation of reports, reminder sending, notifications, answering progress module, chatting facility, operational risk scenario cloning, entire evaluation period cloning, bulk actions (multiple scenario creations, approvals, reverse approvals, deletions and other) and more.
  • Robust governance with workflow, segregated functions, exhaustive audit trail, automatic documentation of modelling assumptions and more.
  • Operational risk scenario mitigation using economic value metrics: NPV of mitigation plans and optimization of insurance programs.
  • Amplifies the influence of the operational risk management function in senior and upper management by using economic value metrics of operational risk scenario impact and its mitigation.
  • End-to-end operational risk scenario analysis process: scenario planning, scenario documentation, scenario evaluation, scenario mitigation and insurance optimization, scenario correlation, Monte Carlo simulation, sensitivity analysis, scenario multi-step aggregation and capital calculation.
Operational risk scenario documentation and evaluation
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. OPERATIONAL RISK SCENARIO DOCUMENTATION AND EVALUATION

Operational risk scenarios sensitivity analysis
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.

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

Automatically generated sensitivity shocks on operational risk scenarios


Operational risk scenario mitigation
SSA 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.

Pre-mitigation risk profile Post-mitigation risk profile

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.

Multiple mitigation plans for per operational risk scenario evaluated


Operational risk scenario insurance optimization
SSA 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.

NPV applying insurance only NPV with both insurance and mitigation plan


Advanced operational risk scenario modelling and bayesian networks
Operational risk operational risk scenarios can be modelled with unlimited number of probability distributions and fit to quantiles and distribution moments and SSA provides multiple means for the evaluation of the goodness of fit.

Different distributions fitted for modelling an operational risk scenario


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

Operational risk scenario using Bayesian Network, pre and after mitigation


Operational risk scenario correlations and Monte Carlo simulation
SSA 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.

Monte Carlo simulation and correlation module
Operational risk scenario correlations and Monte Carlo simulation
Operational risk scenario aggregation and capital determination
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.

Capital aggregation path
Operational risk scenario aggregation and capital determination

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