Should you build or buy Cyber Risk Quantification (CRQ)?
Cyber risk quantification software translates security posture into dollar-denominated loss estimates using methodologies like FAIR, so boards and insurers can compare cyber exposure against other business risks. It serves CISOs, risk officers, and finance teams making capital-allocation and cyber-insurance decisions through scenario modeling and loss benchmarking.
Buy, narrowly. The FAIR method and Monte Carlo tooling are open and internal programs exist, but the loss datasets and calibration vendors sell are what make the numbers defensible, and quantification is governance rather than advantage.
Build it, buy it, or bridge?
When building makes sense
The FAIR methodology itself is open, and pyfair, a maintained Python library, automates the Monte Carlo calculations that turn asset, threat, and control assumptions into a dollar-denominated loss estimate. That means a security or risk team with basic Python skills can run a real quantification program without buying a platform. Netflix and Highmark Health have each documented running exactly that: a spreadsheet-based FAIR program built and scaled internally before either team adopted a dedicated platform. What building doesn't get you is the calibration data: the incident and loss benchmarks vendors compile from claims history and breach databases, which ground your dollar estimates in something more than internal guesswork. Build when your program is scoped to a handful of top scenarios and internal loss estimates are good enough for the audience you're reporting to.
When buying makes sense
Buying earns its place, narrowly, when the number you produce has to survive scrutiny from a board, regulator, or insurer who will ask where the loss figures came from. Vendors like Axio, Kovrr, and Cyberwrite sell calibration data: incident benchmarks and insurance claims intelligence that an internal team can't easily replicate. That data is what makes a quantified risk number defensible rather than a guess dressed up in a spreadsheet. The FAIR math itself is free and open, so you aren't paying for the methodology. You're paying for the evidence behind the inputs. Buy when insurance-tower decisions, board reporting to a skeptical audience, or regulatory requirements demand externally validated numbers. For internal prioritization and rough scenario comparison, a scoped internal FAIR program on open tooling is usually enough, so test that path before signing an enterprise contract.
The desk read
Build-versus-buy analysis for Cyber Risk Quantification (CRQ) is being written. In the meantime, the framework that drives every B4 call is on the B4 Index page.
Frequently asked
Is the FAIR risk-quantification method itself something we have to buy?
No. FAIR is an open methodology, and pyfair is a maintained, open-source Python library that automates its Monte Carlo calculations for free. What vendors sell on top of that open math is calibration data, industry loss benchmarks and insurance claims intelligence, that most internal teams don't have access to on their own.
Can we run cyber risk quantification without buying a platform?
Yes, for a scoped program. FAIR's math and Monte Carlo calculations are available for free through pyfair, and it's common for internal risk teams to run a quantification program on spreadsheets or Python before ever evaluating a vendor. What a self-run program doesn't reproduce is external loss-calibration data, so treat internal FAIR as a starting point, not a full replacement, when regulators or insurers need externally validated numbers.
What are the main cyber risk quantification vendors?
Representative vendors include Axio360, CyberCube, Cyberwrite, Kovrr, Safe Security, which differ mainly in what loss, incident data backs their models rather than in the underlying FAIR-style methodology. B4 Pro includes the category score and the full vendor list.
When does quantified cyber risk actually change a decision?
Mainly around capital allocation and insurance: sizing a cyber-insurance tower, prioritizing remediation spend against other business risks in dollar terms, or answering a board question about how much a breach could cost. If your program is just internal prioritization among security fixes, a scoped internal model is usually enough without a full platform purchase.