Turn probability and impact into actionable exposure numbers. Model controls, confidence, and annualized loss quickly. Download CSV or PDF and share insights securely anywhere.
| Scenario | Probability (%) | Direct Impact | Indirect Multiplier | Mitigation (%) | ARO |
|---|---|---|---|---|---|
| Vendor outage | 30 | 25,000 | 1.3 | 35 | 0.9 |
| Fraud attempt | 18 | 80,000 | 1.1 | 50 | 0.4 |
| Regulatory penalty | 8 | 200,000 | 1.4 | 20 | 0.1 |
Contingency-adjusted exposure represents the most practical budget figure in this calculator. It starts from probability-weighted impact, then reduces for mitigation, scales for confidence, and finally adds contingency. Finance teams often map this value to reserve sizing, risk capital, or project buffers. If contingency is 10%, a 100,000 residual becomes 110,000, making planning resilient to estimation error and execution slippage. Many organizations set thresholds: low below 10,000, moderate 10,000–50,000, and high above 50,000, aligning actions to approval levels and monitoring cadence monthly.
Annualized Loss Expectancy connects exposure factor and event frequency to an asset-value view. LE estimates the portion of the asset at risk per event, while ARO converts that loss into a yearly expectation. ALE is useful for comparing control spend against expected yearly loss. For example, if ALE is 40,000 and a control costs 12,000 per year, payback is strong when the control materially reduces exposure factor or occurrence.
Expected Monetary Value focuses on a single event scenario rather than the entire asset. EMV multiplies the scenario probability by adjusted impact, letting you rank risks by expected cost. Adjusted impact includes indirect costs via a multiplier, which captures downtime, customer churn, legal fees, or operational disruption. When two risks have similar EMV, prioritize the one with higher tail impact or weaker mitigation.
Mitigation effectiveness estimates how much controls reduce expected loss. Residual EMV shows exposure after controls, and it is the best number for tracking improvement over time. If controls improve from 30% to 50%, residual falls by roughly 29% relative to the original EMV. Pair this with confidence to reflect data quality: low-confidence estimates should be treated more conservatively in approvals.
Use the example table as a template and create several scenarios per business unit. Keep assumptions consistent: same time horizon, same currency, and similar multiplier logic. Export CSV for consolidation and sum contingency-adjusted exposures to build a portfolio view. Then stress-test by increasing probability or multiplier for correlated events, such as vendor outages and regulatory penalties occurring in the same quarter.
Use contingency-adjusted exposure for budget and reserves, and ALE for annual planning. Pair the figure with risk level and key assumptions to keep decisions transparent.
Start with historical ratios where possible. If unavailable, list indirect categories (downtime, churn, legal, recovery) and estimate a conservative multiplier, typically 1.0–1.5 for most operational risks.
ARO supports asset-based annual loss (ALE). Probability supports scenario-based EMV for a defined period. Use the metric that matches your governance: annual budgeting versus event-by-event prioritization.
Confidence scales residual exposure between 50% and 100% of the post-mitigation EMV. Lower confidence makes the result more cautious, reflecting limited data or uncertain assumptions.
Run each scenario with consistent time horizon and currency, then export CSV. Compare EMV, residual EMV, and risk score side by side, and rank by exposure and feasibility of mitigation.
No. It is a fast, transparent estimator for consistent scenario analysis. Use it to support discussions, then validate with loss history, simulations, and control testing for high-stakes decisions.
Important Note: All the Calculators listed in this site are for educational purpose only and we do not guarentee the accuracy of results. Please do consult with other sources as well.