Monte Carlo Plus (mc+) is a live API-powered OpVaR engine for UK investment firms and banks — 99.5%, 99.9%, or any required confidence level, fully documented, and aligned with FCA/PRA ICARA/ICAAP expectations.
Aligned with: MIFIDPRU 7 (IFPR/ICARA) · SYSC · FG 21/5 · FG 16/5 · PRA SS1/23 · Basel III / CRD
Regulatory expectations for operational risk modelling are growing for both investment firms (FCA/ICARA) and banks (PRA/ICAAP), but most firms lack the tools to model it rigorously — and the time to build them.
Teams spend weeks building spreadsheets for ICARA instead of acting on the results.
Complex modelling burdenBuilding Monte Carlo simulations, calibrating distributions, and managing correlation matrices requires specialist expertise most firms don't have in-house.
FCA/PRA documentation gapsFirms struggle to demonstrate model governance, validation, and use-test compliance to FCA and PRA supervisors under ICARA and ICAAP respectively.
Annual refresh painUpdating scenarios, re-running simulations, and re-documenting every year consumes disproportionate resources.
Enter your scenarios. mc+ computes the full loss distribution, OpVaR at any required confidence level, diversification benefit, and OpRisk Deltas — instantly, reproducibly, and with full audit trail.
Up to 1,000,000 Monte Carlo iterations run server-side in seconds. No spreadsheets. No local models. Any confidence level — 99.5%, 99.9%, or as required.
Built-in governance framework covering roles, validation, change policy, and data controls — ready for FCA and PRA supervisory review under ICARA and ICAAP.
Support for 100+ scenarios. Enter typical and worst-case losses, likelihoods, and correlations via structured templates. SME inputs captured and challenged automatically.
Sensitivity analysis across severity, likelihood, and correlation — inbuilt OpRisk Deltas identify the largest capital drivers across your entire scenario set.
mc+ uses industry-standard distributions and dependency modelling, fully documented and aligned with FCA/PRA expectations for robust, forward-looking capital modelling under ICARA and ICAAP.
Two-parameter lognormal calibrated from typical loss (mode) and worst-case loss (95th percentile). The most widely-used distribution for operational risk loss modelling.
Each scenario is modelled as a Bernoulli event — either it occurs in the year (1) or it doesn't (0). Annual aggregate severity used for high-frequency scenarios.
Gaussian copula (default) captures linear dependency between scenarios. T-copula available for amplified tail dependency in stress scenarios.
Up to 1,000,000 iterations for stable results, completed in seconds. Outputs sorted to derive OpVaR at 99.5%, 99.9%, or any required confidence level for ICARA/ICAAP.
Aggregate OpVaR incorporating correlation-driven diversification. Minimum 10% correlation floor between all scenarios, consistent with FCA guidance.
Simulation results cross-checked against an analytical OpVaR formula. Parameterisation tested by reproducing typical and worst-case inputs from μ/σ.
mc+ ships with a complete Model Governance Framework covering roles, responsibilities, change policy, and data controls — everything needed to satisfy FCA and PRA supervisory scrutiny under ICARA and ICAAP.
Owns methodology, ensures model remains fit for purpose, maintains documentation and annual refresh.
Implements model logic, maintains code, ensures computational accuracy and version control.
Performs independent validation every 3 years, challenges assumptions, and tests stability.
Provide scenario inputs — typical and worst-case losses, likelihoods, and correlation estimates.
Approves model assumptions, results, and material changes. Methodology changes require committee sign-off.
Approves the ICARA including model outputs. Board-level accountability for operational risk capital.
mc+ is built from the ground up to meet FCA and PRA expectations for robust, forward-looking, and proportionate operational risk modelling — covering both ICARA (investment firms) and ICAAP (banks) under the respective regulatory regimes.
MIFIDPRU 7 (IFPR/ICARA) — capital adequacy for FCA-regulated investment firms; mc+ directly supports the operational risk capital component of the ICARA process
PRA Pillar 2 / ICAAP — Internal Capital Adequacy Assessment Process for PRA-regulated banks and building societies; mc+ provides the OpVaR at 99.9% or any required confidence level
SYSC (Systems & Controls) — model governance framework satisfies FCA/PRA expectations for robust risk management infrastructure
FG 21/5 (Wind-down planning) — operational risk scenarios include wind-down stress events relevant to both investment firms and banks
FG 16/5 (Operational risk frameworks) — scenario-based approach and SME challenge process aligned with FCA/PRA guidance
PRA SS1/23 (Model risk — best practice) — governance, validation, and documentation standards adopted as best practice for both FCA and PRA supervised firms
Basel III / CRD (Standardised/AMA) — mc+ methodology consistent with Basel operational risk capital principles for internationally active banks
The model satisfies FCA and PRA use-test requirements — it must be genuinely embedded in business decision-making, not produced solely for regulatory compliance.
Primary use — annual operational risk capital calculation for ICARA (investment firms) and ICAAP (banks)
OpVaR outputs inform board-level risk appetite thresholds and tolerance statements
Explore how changes to individual scenarios affect aggregate capital requirements
T-copula amplification, reverse stress tests, and increased correlation scenarios
Use modelled loss distributions to calibrate appropriate insurance cover levels
Structured outputs for operational risk committee and board reporting packs
Every mc+ model is subject to independent validation covering conceptual soundness, parameterisation, and stress testing — satisfying FCA and PRA model risk expectations.
Lognormal severity and Bernoulli frequency confirmed as industry-standard; copula-based dependency modelling assessed as appropriate
SME inputs challenged for plausibility using structured impact and likelihood templates; consistency checks applied
Typical and worst-case loss inputs reproduced from derived μ/σ parameters to verify calibration accuracy
Analytical OpVaR formula used as an independent cross-check against simulation output
Severity, likelihood, and correlation sensitivity tested — inbuilt OpRisk Deltas identify the largest capital drivers and assess model stability across all scenarios
Where historical annual loss data exists, modelled distribution compared against actual losses
T-copula amplification, increased correlation scenarios, and reverse stress tests applied to validate tail behaviour
Request a demo of mc+ and see how it fits into your ICARA or ICAAP process.
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