APIR Insurance Score™
The 0–100 rating that bridges AI compliance posture and risk pricing, the underwriting data layer for E&O, professional liability, and cyber policies covering AI deployments. APIR produces the rating and the evidence; licensed carriers and brokers price and bind any policy, not APIR.
Eight sub-scores
Behavioral Reliability
Action verification rate, rule compliance, high-risk action share
Incident History
Critical + open incidents, resolution record
Compliance Coverage
Framework compliance status (EU AI Act · NIST · ISO 42001)
Drift Stability
Behavioral drift, fingerprint divergence, audit anomalies
Containment Readiness
Ghost Audit coverage, active monitoring, audit depth
Data Governance
Trust score contribution, platform registration, compliance
Transparency
Traceability: platform, model identity, fingerprint baseline
Human Oversight
Decision authority model, human review rate, monitoring
Scoring formula
Each sub-score is 0–100. The Insurance Score is the weighted blend, rounded to one decimal:
insurance_score = round₁( Σᵢ (sub_scoreᵢ × weightᵢ) ) where Σᵢ weightᵢ = 1.00
Rating-agency grade bands map the score to an underwriting outcome:
≥ 90
Exceptional: strongest underwriting position
≥ 85
Excellent
≥ 80
Strong: standard terms expected
≥ 75
Good
≥ 70
Adequate
≥ 65
Certifiable minimum: substandard terms
≥ 55
Weak: high-risk tier
≥ 45
Very weak
≥ 35
Restricted: generally excluded
≥ 0
Uninsurable in current state
Insurability tiers & certification
The score also maps to an insurability tier, the vocabulary brokers see on every APIR surface:
Certification threshold: 65. Agents scoring grade B / substandard-or-better are eligible for an APIR Insurability Certificate, issued only by a human-triggered issuance call, valid 365 days, publicly verifiable.
Note: the APIR Insurance Score is 0–100. The FICO-style 300–850 scale belongs to the separate APIR Agent Credit Bureau product.
Worked example
An agent with:
behavioral_reliability: 82 (weight .20) incident_history: 75 (weight .20) compliance_coverage: 90 (weight .15) drift_stability: 85 (weight .15) containment_readiness: 100 (weight .10) data_governance: 80 (weight .08) transparency: 70 (weight .07) human_oversight: 88 (weight .05)
Produces:
insurance_score = 82×.20 + 75×.20 + 90×.15 + 85×.15 +
100×.10 + 80×.08 + 70×.07 + 88×.05
= 16.4 + 15.0 + 13.5 + 12.75 + 10.0 + 6.4 + 4.9 + 4.4
= 83.4 → Grade A · insurability: standardA broker pricing an E&O policy for this agent sees Grade A / standard tier: insurable on standard terms, with GL AI exclusions (CG 40 47/48) to verify on the existing policy.
Reproducibility
Every agent_insurance_scores row carries the methodology_version that produced it, and every rescore appends to an immutable score history. A broker pulling a score knows exactly which version of this rubric was applied; historical scores stay comparable even after methodology updates. One engine computes every score, there is no second code path.
Citing this document
APIR Intelligence. (2026). APIR Insurance Score Methodology v1.1.0. https://apir.ai/insurance/methodology