Insurance Calibration
Public overview of UAIF-CAL-INSURANCE-v1.0; the operational package is controlled.
Purpose and scope
Underwriting, pricing, claims, fraud, customer service and insurance operations; banking is separately calibrated.
The package calibrates UAIF classification for sector context without replacing the UAIF Technical Specification or applicable law.
Status and validation boundary
Version 1.0 is provisional pending empirical inter-rater validation. The source document states that provisional weights must not be used as the sole basis for regulatory reporting, certification or consequential decisions.
Public information
- Document reference: UAIF-CAL-INSURANCE-v1.0
- Version: v1.0 provisional
- Public scope and exclusions
- Method based on public regulatory material, research and recognised severity frameworks
- Known validation and legal-review limitations
Sector risk context
Insurance AI determines who can obtain cover, at what price, and whether a claim is paid. Failures concentrate in financial and rights dimensions: discriminatory underwriting, wrongful automated claims denial, biased premium pricing, and false-positive fraud flagging directly affect access to insurance and financial security. Privacy exposure is high because insurers process health data, telematics, behavioural profiling, and full financial records. Physical and environmental harms are largely indirect, arising only where denied or delayed cover affects access to care.
1.1 Applicable Regulations
• EU AI Act — Annex III high-risk: life and health insurance risk-assessment and pricing AI [T1]
• GDPR Articles 9 (special-category data), 22 (automated decision-making) [T1]
• EIOPA AI Governance Principles (2021) and supervisory expectations [T2]
• NAIC Model Bulletin on the Use of AI Systems by Insurers (2023) [T2]
Extracted from the source sector profile. Detailed calibration and operational material remains controlled.
Public sector orientation
Representative classification concerns include underwriting and pricing, claims, fraud detection, discrimination, customer explanation, privacy and financial harm. These themes help teams scope incident intake and analysis; they are not calibration weights, legal conclusions or an exhaustive risk list.
Use with the UAIF layers
- Establish incident identity, provenance and remediation state.
- Separate cause, manifestation, acute harm and chronic-harm proxies.
- Apply severity and context logic with the provisional calibration status visible.
- Record sector and jurisdiction metadata for human review and routing.
- Preserve uncertainty, contrary evidence and the version of every referenced artifact.
Controlled resource
The detailed package, calibration weights, scoring implementation, evidence logic and maintenance material are confidential commercial resources governed by UAIF-LIC-003 and applicable GEL terms.
Notably Absent
No empirical validation result, regulatory approval, certification status, universal sector applicability or legal-reporting determination is claimed.