| name | cyber-risk-quantification |
| description | Translate technical security risk into business and financial terms — top risk scenarios, likelihood × impact, a risk register, and (where useful) quantified loss ranges (FAIR-aware) — to support executive decisions on treat/transfer/accept. Use to communicate or prioritize cyber risk for leadership. |
Goal
Cyber risk expressed the way executives make decisions: which scenarios matter, what
they could cost the business, how that compares to risk appetite, and what to do
(treat / transfer / accept).
Steps
- Identify risk scenarios — concrete, business-relevant loss events (e.g.
"ransomware halts operations for N days", "breach of customer PII") rather than raw
vulnerabilities. Derive from
threat-modeling, findings, and threat intel.
- Estimate likelihood and impact — qualitative (heat map: likelihood × impact)
and, where the decision warrants, quantitative loss ranges (a FAIR-style estimate:
frequency × magnitude, expressed as a range, not false precision).
- Compare to appetite — plot residual risk against the org's stated risk
appetite/tolerance; flag what exceeds it.
- Recommend treatment — for each significant risk: mitigate (and the control +
cost), transfer (insurance/contract), or accept (with owner and sign-off).
- Maintain the register — owner, current vs. residual risk, treatment, status,
review date; track trend over time.
Output
A risk register + a heat map, plus quantified top risks (loss ranges) where relevant,
and treatment recommendations. Use security-reporting; visualize the heat map with
security-diagramming:infographic. Feeds security-strategy and board-deck.
Notes
Quantify in ranges, not false precision — "likely $2–8M annual loss exposure" beats a
single fabricated number. Frame risks as business loss scenarios, not CVEs. Tie every
significant risk to an explicit treatment decision and an accountable owner; accepted
risk must be consciously accepted, not defaulted.