Cyber Risk Quantification Calculator 2026
FAIR-based annualized loss expectancy (ALE) calculator with Monte Carlo range estimation. Built for board-level risk reporting and security investment justification.
The FAIR Model Simplified
Threat Event Frequency
How often?
Annual Rate of Occurrence (ARO)
x
Loss Magnitude
How much?
Single Loss Expectancy (SLE)
= Risk in Dollar Terms
Annualized Loss Expectancy (ALE)
FAIR (Factor Analysis of Information Risk) replaces subjective risk matrices with quantified, dollar-denominated risk. Instead of saying "ransomware risk is high," you say "ransomware risk costs us $588,000 per year in expected losses." This is the language CFOs, boards, and auditors understand.
Multi-Scenario ALE Calculator
Add up to 5 risk scenarios. Use pre-filled industry averages or enter your own estimates.
Risk Quantification FAQ
What is FAIR and why should I use it?
FAIR (Factor Analysis of Information Risk) is the only international standard for cyber risk quantification (OpenFAIR). It replaces subjective heat maps with dollar-denominated risk estimates that CFOs and boards understand. Over 90% of Fortune 100 companies use some form of FAIR-based risk quantification.
How accurate are ALE estimates?
ALE estimates are directionally accurate, not precisely predictive. The value is in comparing risks to each other and to proposed investments, not in predicting exact losses. Using Monte Carlo ranges (10th/50th/90th percentile) communicates uncertainty honestly.
Where do SLE and ARO numbers come from?
SLE (Single Loss Expectancy) comes from our individual calculators (ransomware, breach, downtime, etc.) which use IBM, Ponemon, and Verizon data. ARO (Annual Rate of Occurrence) comes from industry frequency data. Both should be adjusted to your organization's specific context.
How do I present this to the board?
Lead with the total ALE in dollars. Then show the control cost justification: 'We face $2.1M in annual expected losses. A $400K investment reduces this to $1.47M, a net savings of $230K per year.' Boards respond to dollars, not risk colors.
What is Monte Carlo simulation?
Monte Carlo uses thousands of random samples from probability distributions to model uncertainty. Instead of a single ALE number, it produces a range: 'There is a 90% chance our annual losses will be between $X and $Y.' Our simplified version provides 10th, 50th, and 90th percentile estimates.
How often should I update risk quantification?
Quarterly at minimum, and after any significant incident or major infrastructure change. Many mature organizations run continuous risk quantification integrated with their SIEM and asset management data. At minimum, update annually when IBM CODB and Verizon DBIR release new data.