Quantify risk in rupees and dollars — not red, amber, green
A Monte-Carlo FAIR engine turns risk into loss-exposure ranges leadership actually understands, with risks auto-correlated from your live findings.
A 5x5 heat map tells a board nothing about how much a risk could cost. Comply runs Monte-Carlo simulations on FAIR inputs to express risk as annualized loss exposure — and connects the register to reality, so a failing control or a degrading vendor automatically raises and updates the related risk.
Monte-Carlo / FAIR
Model frequency and magnitude to produce P50/P95 loss-exposure ranges — defensible numbers for the board.
Auto risk correlation
Findings, vendor degradations and device drift automatically raise and update the risks they affect.
Treatment & KRIs
Track treatment plans, residual risk and key risk indicators over time, not just at audit.
Board-ready reporting
Turn the register into clear, quantified reports for leadership and auditors in a click.
Up and running fast
Build the register
Start from templates mapped to your frameworks.
Quantify
Enter FAIR inputs; Comply simulates loss exposure.
Track
Risks update automatically as your posture changes.
- Loss exposure in ₹ / $, not colours
- Risks linked to live findings & vendors
- KRI and residual-risk tracking
Common questions
FAIR (Factor Analysis of Information Risk) is the standard for quantifying cyber risk in financial terms. Comply runs Monte-Carlo simulations on FAIR inputs to produce loss-exposure ranges.
No — qualitative scoring is supported too. Quantification is there when leadership needs a number rather than a colour.
Explore the rest of the platform
26 modules, one system. Here's where teams go next.
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Free tier: 1 framework · 10 workers · 2 connectors. Upgrade only when you grow.