FairCRQ review

Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

FairCRQ is a browser-based cyber risk quantification utility from Veptr.ai, intended for organizations that need to assess potential cyber losses and communicate them to decision-makers. It models scenarios such as ransomware, data breaches and supply-chain attacks using OpenFAIR factors and Monte Carlo simulation. The tool is described as usable without registration, making it an accessible option for solo users through enterprise teams seeking an initial, structured estimate rather than a full risk-management platform.

Its core output is more than a single headline figure: FairCRQ provides annualised loss expectancy, percentile distributions, a loss exceedance curve, scenario rankings and a board-ready summary. Each scenario uses 10,000 Monte Carlo iterations. Estimates draw on organizational revenue, employee count and industry, as well as security maturity and security-tool coverage. Users can optionally refine the model with past incidents, downtime costs, sensitive-record counts, insurance coverage, security budgets and regulatory selections. This breadth of calibration can help tailor estimates, but results will depend on the quality and relevance of the organizational information entered.

FairCRQ is a focused choice for teams that want OpenFAIR-based scenario estimates and clear reporting without an account requirement or paid plan. It is less suited to buyers looking for verified integrations, API access or a broader cyber-risk workflow that connects quantification to other systems. The vendor describes the project as independent and says computations are performed server-side in memory while also saying information is not stored or transmitted; those descriptions leave the handling of information unclear. Organizations with strict data-handling requirements should weigh that uncertainty before entering sensitive inputs, while teams comfortable with a standalone web utility may find its board-oriented outputs useful.

FairCRQ pros and cons

• Where it wins
  • OpenFAIR estimates include 10,000 Monte Carlo iterations per scenario
  • Shows annualised loss expectancy, percentiles and a loss exceedance curve
  • Produces scenario rankings and a board-ready risk summary
• Where it doesn't
  • Estimates depend on organizational and security inputs, with calibration optional
  • Focused on cyber-loss quantification rather than broader risk management
  • No verified integrations or API access

FairCRQ fact sheet, pricing and score →

Advertiser disclosure: iTechGuides is reader-supported. Vendors can pay for top positions in our rankings and for a place on other products' pages, and we may earn a commission when you click some links. Bought places stand at the number bought; this page and our disclosure say so. Paying vendors may get a fuller, more detailed review from our editors, and that review can change their score. How we rank.

Last updated 7 Oct 2026 · How we research and update