RisqRadar replaces subjective heat maps with Monte Carlo simulations that quantify your actual exposure. Finally answer: "What could a breach really cost us?"
They want to know: How much could we lose? How likely is it? How much should we spend to prevent it?
| Risk Scenario | Expected Loss | 95th Percentile |
|---|---|---|
| Ransomware Attack | $2.4M | $8.2M |
| Data Breach | $1.8M | $12.1M |
| Insider Threat | $0.9M | $3.4M |
| DDoS Attack | $0.3M | $0.9M |
Built on QRM™ (Quantified Risk Model) — our proprietary methodology that combines proven frameworks into a practical, defensible approach.
Federal standard for risk assessment
Proven techniques to fix overconfidence
Statistical modeling of uncertainty
Benchmarks and guidance at every step
| Factor | What It Measures |
|---|---|
| TPThreat Probability | How often attackers try |
| ASRAttack Success Rate | How often they succeed |
| ISImpact Severity | Direct costs when they do |
| CICascading Impact | Secondary costs that follow |
| IMImpact Multiplier | Probability of those secondaries |
The Result
ALE = (TP × ASR) × (IS + CI × IM)
Annual Loss Expectancy (ALE) — A defensible dollar amount your board can act on.
Not "high risk." Not a heat map. A number.
Start with what keeps you up at night—ransomware, data breaches, insider threats. Our AI Scenario Generator helps you get started in minutes.
Most experts are overconfident. Our AI Calibration Coach ensures your 90% confidence intervals are actually right 90% of the time.
Monte Carlo analysis runs 10,000+ iterations using your estimates, producing probability distributions instead of single-point guesses.
Prioritize investments by ROI, report to the board in their language, and know exactly how much risk reduction you're buying.
Other tools let you input estimates and run simulations. Garbage in, garbage out.
RisqRadar requires calibration training before you create risk assessments. Our AI Coach detects cognitive biases and helps you give estimates that match your actual accuracy.
Result: When you say 90% confident, you're actually right 90% of the time.
The AI Estimation Assistant provides:
But it never gives you a single "correct" answer. You remain in control.
QRM explicitly maps to NIST Special Publication 800-30. This means:
| Enterprise CRQ | RisqRadar | |
|---|---|---|
| Annual Cost | $50K - $200K | $99/month |
| Implementation | 3-6 months | 30 minutes |
| Consultants | Required | No |
| Calibration | External ($5K+) | Built-in |
AI that guides your judgment without replacing it. Get benchmarks, catch biases, and generate reports—all while you stay in control.
Analyzes your calibration performance, detects cognitive biases (anchoring, overconfidence, availability), and provides personalized exercises to improve your estimation accuracy.
Available on every input field. Get industry benchmarks, validation, and decomposition help. References authoritative sources like Verizon DBIR and IBM Ponemon.
Analyzes your organization profile and recommends relevant risk scenarios with pre-populated QRM estimates. Accelerates time-to-value from weeks to minutes.
Generates board-ready talking points, executive summaries, and Q&A preparation. Select your audience (Board, Executive, Technical, Audit) and get tailored content.
Creates fresh calibration questions on demand. You'll never see the same question twice during annual recertification.
"When people give 90% confidence intervals, they typically contain the true answer only 50-60% of the time."
QRM maps directly to NIST 800-30 Rev. 1, the federal standard for conducting risk assessments. This provides:
AI Estimation Assistant references:
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Full-featured risk quantification
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Join security leaders who speak the board's language—dollars and probabilities, not colors and gut feelings.