FAIR Risk Estimator · All tools · by CreativeCyber
◆ RiskSage AI

FAIR Risk Estimator

Three inputs. Instant Annualised Loss Expectancy (ALE) band, board-ready narrative, and BFSI peer percentile — powered by the FAIR™ methodology.

Factor Analysis of Information Risk (FAIR) · BFSI-calibrated
Threat Event Frequency (TEF) 12 /yr

How many times per year does a credible threat actor attempt this attack type against your organisation? (Includes unsuccessful attempts.)

1/yrMonthlyWeeklyDaily
Vulnerability — Control Gap (%) 35%

What percentage of threat events succeed given your current controls? 0% = perfect controls. 100% = no controls. BFSI average: 25–45%.

1%25%50%75%100%
Loss Magnitude per Event (₹ Lakhs) ₹150L

Total loss per successful event: direct costs (investigation, notification, remediation) + indirect (fines, reputational, operational). SEBI CSCRF breach average: ₹80–500L.

₹5L₹500L₹1000L₹5000L
Annualised Loss Expectancy (ALE)
TEF × Vuln
Loss Events/yr
BFSI Peer %ile
of firms your size
Risk Tier
Board classification
BFSI Peer Distribution
LowModerateHighCritical
Board Narrative
Methodology: ALE = TEF × Vulnerability × Loss Magnitude. Based on FAIR™ (Factor Analysis of Information Risk) framework. Peer percentiles calibrated against RBI/SEBI incident disclosures and DSCI BFSI breach cost studies (2022–2024). This is an estimation tool — engage a qualified risk professional for board-level risk quantification.

RiskSage AI quantifies cyber risk across your full attack surface — SEBI CSCRF posture, FAIR modelling, and board-ready risk dashboards.

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RiskSage extends this single-scenario model to Monte Carlo simulation, full portfolio risk aggregation, and board/regulator-ready risk quantification across your entire asset inventory.

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Invite-only · Provisioned by CreativeCyber

AI-native cyber risk platform for Indian BFSI