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Cyber Risk Quantification · FAIR · Monte Carlo · Financial Modelling

Stop reporting risk in
red, amber, green.

Cyber Risk Quantification (CRQ) using the FAIR model and Monte Carlo simulation. We express your cyber exposure in rupees and dollars — not heat-map colours — so your board, CFO, and insurer can make decisions the way they make every other risk decision.

FAIR · ISO 31000
Standards-Aligned
10k+ sims
Per Risk Scenario
CFO-Ready
Reported in ₹ / $
insec@crq ~ risk-model · client.com · v4
◈ Annualized Loss · Monte Carlo · 10k runs
Expected ALE
18.4Cr
▼ after controls: ₹7.2 Cr
P90 Loss
62Cr
tail-risk · 1-in-10
LEF · avg/yr
3.2/yr
loss-event frequency
Control ROI
4.1×
EDR + MFA + backups
Loss distribution · ₹ Cr10k iterations
0102550100+
Ransomware event₹11.2 Cr/yr
Large data breach₹4.8 Cr/yr
Extended outage₹1.6 Cr/yr
Insider IP theft₹0.8 Cr/yr
Residual (post-control)₹7.2 Cr
83%
of boards want cyber risk in financial terms
62%
of CISOs still report using heat maps only
3.2×
higher budget approval with quantified asks
₹ / $
the only language that aligns CISO + CFO
// The Problem

The board asks for value. You hand them colour.

Traditional risk registers aren't wrong — they're incomplete. When every decision your organisation makes is in rupees, speaking a different language on cyber leaves you at a permanent disadvantage.

◈ QUALITATIVE

Traditional Heat Maps

  • "High" on one team's scale = "Medium" on another's
  • Board can't compare cyber to business risk
  • No way to calculate ROI of controls
  • Insurers can't underwrite against colour
  • Multiple "critical" risks with no prioritisation
  • No defensible methodology for external audit
  • Can't model "what if we add control X"
  • Decisions reduced to intuition & seniority
◈ QUANTITATIVE · FAIR

Cyber Risk Quantification

  • "Ransomware costs ₹11 Cr/yr · ₹62 Cr at P90"
  • Cyber risk comparable to all other enterprise risk
  • Every control investment shows ROI
  • Insurer can quote against defensible numbers
  • Clear top-1, top-2, top-3 prioritisation
  • FAIR is an Open Group standard · auditable
  • Scenario modelling: "what if we add MFA?"
  • Evidence-based CapEx/OpEx justification
// The FAIR Model

An Open Group standard. Not magic.

FAIR (Factor Analysis of Information Risk) decomposes risk into measurable components. Each is estimated as a range (PERT distribution), not a single number, then run through Monte Carlo simulation.

◈ RISK · Annualized Loss Expectancy (ALE)
Loss Event Frequency · LEF

How often a loss event occurs per year

Loss Magnitude · LM

Financial magnitude when it does occur

Threat Event Frequency

How often adversary attempts

Vulnerability

Probability attempt succeeds

Primary Loss

Direct impact · response · recovery

Secondary Loss

Fines · legal · reputation · customer

ALE = LEF × LM · simulated 10,000× across PERT ranges · output: loss distribution
// What We Deliver

From risk register to board deck.

Quantified Risk Register

Your existing risk register translated into financial exposure per scenario, with tail-loss percentiles.

  • Top-10 scenario modelling
  • Annualized Loss Expectancy per risk
  • P50 / P90 / P99 tail-loss percentiles
  • Aggregation across portfolio
  • Ranking vs. enterprise-risk register

Control ROI & Portfolio Optimisation

Every proposed investment scored against risk reduction per rupee spent.

  • Before/after control modelling
  • Cost-of-control vs. risk-reduction
  • Roadmap optimisation
  • Quick-win identification
  • CapEx / OpEx business cases

Board & Regulator Reports

Reports that boards read and regulators accept. No jargon, no heat maps.

  • Board-deck templates in your format
  • CFO / Audit Committee briefs
  • Cyber-insurance submission pack
  • Regulator-facing narrative
  • Quarterly trend reporting

Scenario Library

Pre-built quantification scenarios mapped to your industry & threat landscape.

  • Ransomware · ALE + worst-case modelling
  • Data breach · DPDP / GDPR fine inclusion
  • Insider IP theft · competitive impact
  • DDoS / outage · revenue-per-hour
  • Third-party / supply-chain compromise

Insurance & Retention Optimisation

Right-size your cyber-insurance tower with defensible numbers — not guesswork.

  • Coverage-vs-exposure gap analysis
  • Retention (deductible) optimisation
  • Limit-adequacy modelling
  • Premium-negotiation support
  • Renewal-questionnaire responses

Continuous Risk Program

Not a one-off report. A living program that updates as your environment & threat landscape evolve.

  • Quarterly re-quantification
  • Trigger-based re-modelling
  • New-scenario authoring
  • Threat-intel integration
  • Board-reporting cadence
// Methodology

Repeatable. Defensible. Open-standard.

We follow Open FAIR, ISO 31000, and NIST SP 800-30 — so the numbers hold up in audit, in litigation, and in insurance negotiations.

01 · SCOPE

Crown Jewels & Scenarios

Critical assets, business processes, data classifications, scenarios to model, loss categories.

02 · DATA

Data Collection

Incident history, industry benchmarks, control posture, financial data, regulatory context.

03 · FAIR

FAIR Decomposition

Each scenario broken down: LEF → TEF + Vulnerability · LM → Primary + Secondary.

04 · CALIBRATE

Calibrated Estimates

Workshops with your SMEs · calibration-trained estimates · min / most-likely / max ranges.

05 · SIMULATE

Monte Carlo Simulation

10,000+ iterations per scenario · output loss distributions · percentiles · sensitivity analysis.

06 · MODEL

Control Modelling

Before/after scenarios for each proposed or existing control · reduction per rupee spent.

07 · AGGREGATE

Portfolio Aggregation

Total cyber exposure across scenarios · comparison with other enterprise-risk categories.

08 · REPORT

Board-Ready Report

Executive narrative, CFO appendix, technical methodology pack, insurer submission, regulator-ready.

09 · REFRESH

Ongoing Refresh

Quarterly re-run · threshold-triggered re-modelling · scenario library expansion · trend reporting.

// Standards & References

Open standards. Defensible methodology.

Open FAIR

Open Group standard (O-RT / O-RA).

ISO 31000

Risk-management principles.

NIST SP 800-30

Guide for risk assessments.

NIST SP 800-39

Managing info-security risk.

NIST CSF 2.0

ID.RA · ID.IM · GOVERN function.

COSO ERM

Enterprise-risk integration.

ISO 27005

Info-security risk management.

FAIR-CAM

Controls-analytics model.

// What Changes After CRQ

Cyber enters the boardroom as a business risk.

CISO ↔ CFO Alignment

Your CISO stops arguing about risk colour. Your CFO starts making defensible investment decisions. Same language.

Better Insurance Terms

Insurers reward organisations with defensible numbers. Expect meaningful premium reduction & better limits.

Security Spend ROI

Every security investment comes with measured risk-reduction · your budget asks pass first time, every time.

Regulator-Ready Narrative

DPDP / RBI / SEBI regulators increasingly expect quantified risk assessments · you arrive prepared.

Tracked Trend Over Time

Quarterly re-quantification shows whether your exposure is dropping. Evidence, not claims.

Defensible in Litigation

FAIR is an Open Group standard · reports stand up in regulatory investigations & shareholder litigation.

// Engagement Timeline

Baseline in 6-8 weeks.

WEEK 0

Scoping & NDA

Crown jewels, top scenarios, SME availability, loss categories, data-privacy ground rules.

WEEK 1-2

Data Collection

Incident history, financial data, control posture, industry benchmarks, regulator context.

WEEK 2-3

FAIR Decomposition

Scenario breakdown · LEF + LM factor trees · data source mapping per node.

WEEK 3-4

Calibration Workshops

SME-calibrated ranges for each factor · PERT parameters · assumption documentation.

WEEK 4-5

Simulation & Modelling

Monte Carlo runs · control-scenario modelling · portfolio aggregation · sensitivity.

WEEK 6

Reporting & Board Brief

Executive summary · technical appendix · board-deck · insurer-pack · live walkthrough.

QUARTERLY

Refresh Cadence

Targeted re-runs · new-scenario authoring · trend reports · board reporting.

// FAQ

What leaders ask before they commit.

Is FAIR credible? How do I know the numbers are real?
FAIR is an Open Group international standard (O-RT, O-RA) — the same body that standardises TOGAF. It's the most widely adopted quantitative model in cyber, used by Fortune 500 CISOs and increasingly referenced by regulators. The methodology is transparent: every number has a source, every assumption is documented, every Monte Carlo run is reproducible.
But we don't have enough data to quantify.
You do — you just need to know how to use it. FAIR works with calibrated estimates from SMEs when direct data is sparse (and it usually is). Industry benchmarks, incident reports, and your own history fill the gaps. The output is ranges with percentiles, not false precision. The goal isn't perfect accuracy; it's defensible decision-making.
Does this replace our existing risk register?
No — it upgrades it. Your existing register stays as the inventory. CRQ adds financial exposure per risk, comparison with enterprise-risk categories, and control-ROI modelling. Many clients run both in parallel until the CRQ view earns trust — then the register evolves.
Will the insurer actually accept this?
Yes, and increasingly they prefer it. Major cyber-insurance carriers (Beazley, Allianz, Chubb, Howden, Marsh) have specialist underwriters who recognise FAIR outputs. Defensible numbers lead to better limit conversations, reduced exclusions, and sometimes lower premiums. We can help prepare submissions.
Which tools do you use?
We use RiskLens and FAIR-U for standard engagements. For custom needs, we build proprietary Monte Carlo models in Python / R / Excel+@Risk. Tooling is always secondary to methodology — we care more that the math is defensible than which software prints the chart.
How often should we re-quantify?
Typical cadence is quarterly board-cycle refresh, with trigger-based re-modelling when something material changes (major incident, new critical system, regulatory shift, M&A, new threat). We set up the trigger rules during engagement.
How much does it cost?
Baseline engagement (top 5-10 scenarios, 6-8 weeks) typically ₹10L–₹25L. Enterprise program with portfolio modelling, insurer packaging, and quarterly refresh from ₹40L/year. Fixed quote after scoping call.
Can you train our team to do this internally?
Yes. Many clients prefer capability transfer over a recurring service. We deliver the engagement, then train your risk / CISO team on calibration, modelling, and reporting so future cycles run in-house. Support retainer available.
// Get Started

Report cyber risk the way your CFO reports every other risk.

Book a confidential 30-minute scoping call. We'll agree scope, scenarios, and stakeholders. Fixed quote inside 48 hours.