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FAIR Risk Quantification

Z Cyber's FAIR Risk Quantification engagement decomposes your top loss scenarios using Factor Analysis of Information Risk, the open standard for expressing cyber risk in financial terms, and produces governed dollar-based estimates in our AI-native GRC platform alongside treatment options ranked by return. Instead of arguing about whether a risk is 'high' or 'medium', your leadership compares loss exposure against the cost of reducing it, and security spending gets defended the way every other investment does.

Scope

What's Included

Scenario selection workshop for your highest-stakes loss events

FAIR taxonomy decomposition per scenario, with documented factor estimates

Governed dollar-based loss exposure estimates with documented assumptions

Treatment portfolio ranked by exposure reduction per dollar spent

Board-ready quantification briefing

Model handoff in our AI-native GRC platform so exposure recomputes as controls change

Who Does the Work

The team behind every engagement

Executive Security Advisor

Selects scenarios with your leadership, reviews model assumptions, oversees the report, and presents the results.

Senior Security Consultant

Builds the FAIR decompositions and calibrates the factor estimates with your data.

Security Analyst

Gathers loss data inputs and maintains scenario documentation in our AI-native GRC platform.

AI-Native GRC Platform

Computes the dollar-based estimates, recomputes exposure when controls change, and generates the treatment ROI view.

Who This Is For

CISOs and CFOs who need to defend a security budget, boards that want cyber risk expressed like other enterprise risks, and organizations choosing between competing security investments.

Our Process

1

Select

Identify the loss scenarios that matter most: the events your leadership actually worries about, tied to real systems and data.

2

Model

Decompose each scenario into loss event frequency and magnitude, calibrated with your environment's data and industry inputs.

3

Quantify

Compute loss exposure in dollars from the calibrated factors, so every figure traces back to a documented assumption rather than a color on a heat map.

4

Decide

Rank treatment options by exposure reduction per dollar and hand leadership a portfolio they can fund with confidence.

Frequently Asked Questions

What is FAIR?

Factor Analysis of Information Risk, the leading open standard for quantifying cyber risk in financial terms. FAIR decomposes risk into loss event frequency and loss magnitude, which makes cyber risk comparable to the other risks your business already manages in dollars.

Is quantification just guessing with extra steps?

No. Calibrated estimation against a documented taxonomy is how insurance, finance, and engineering handle uncertainty. Every factor in the decomposition is documented and defensible, which is more than a color on a heat map can say.

What data do you need from us?

Asset and system context, incident history if available, and access to the people who understand your loss scenarios. Where internal data is thin, we calibrate with documented industry inputs and state the assumptions explicitly.

Does the model go stale after the engagement?

The models live in our AI-native GRC platform and recompute as your control state changes. Exposure stays current between assessments instead of expiring the day the report lands.

Ready to see where you actually stand?

Book a 30-minute briefing with the team that would run your program. We'll assess your needs, scope the right engagement, and follow up with a fixed-fee proposal - no pressure, no generic pitches.

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