Scorecard/AI Underwriting Company

AI Underwriting Company

Data gathering in process

Combines audits, standards, and insurance to enable enterprises to confidently deploy AI agents. Created the AIUC-1 safety standard.

HQUS
Est2024
Size11-50
EU AI ActLimited Risk
aiuc.com
Score
70.0 / 100
Evidence
6 items

Industry-leading safety practices with comprehensive governance and technical safeguards.

Strengths:Governance Maturity, Technical Safety, Risk Assessment, Regulatory Readiness, External Engagement
Focus Areas
ai governanceai safety toolinginsurancecompliance

Security Assessment

Security-relevant indicators for vendor evaluation

Security Posture
69
TS-01dim: 68
Red Teaming & Pre-deployment Testing
Adversarial testing before deployment
TS-05dim: 68
Robustness & Adversarial Resilience
Resistance to adversarial attacks
RA-01dim: 70
Sector-Specific Risk Assessment
Risk analysis for deployment context
RA-03dim: 70
Dual-Use & Misuse Risk
Dangerous capability awareness
RA-07dim: 70
Incident History & Track Record
Past incidents and response quality
EE-04dim: 60
Vulnerability Disclosure Program
Bug bounty or CVE reporting process
Incident History
AI Underwriting Company incident records sourced from AIAAIC Repository and public reporting.
Integration: AIAAIC, OECD AI Incidents Monitor
Third-Party Audits
External audit reports, SOC 2 attestations, and ISO certifications verified where published.
Sources: Company filings, registry lookups
CVE & Disclosures
Known vulnerabilities and security advisories from NVD, GitHub Security Advisories, and vendor pages.
Sources: NVD, GHSA, vendor disclosure pages

Dimension Breakdown

GM
Governance Maturitymedium
Published policies, corporate structure, safety mandate, whistleblowing, executive commitment.
72
1 evidence items
GM-01
TS
Technical Safetymedium
Benchmarks, adversarial robustness, fine-tuning safety, watermarking, model cards, research output.
68
1 evidence items
TS-01
RA
Risk Assessmentlow
Dangerous capability evaluations, thresholds, external testing, bug bounty, halt conditions.
70
1 evidence items
RA-01
RR
Regulatory Readinesslow
ISO 42001, EU AI Act compliance, GPAI obligations, international commitments, incident reporting.
75
2 evidence items
RR-01RR-05
EE
External Engagementmedium
Survey participation, research support, transparency, behavior specs, open-source contributions.
60
1 evidence items
EE-01

Social Impact & Safety Profile

Moderate

AIUC builds governance tooling that helps organisations assess and manage AI risk, directly contributing to safer AI deployment. Their underwriting framework embeds social impact considerations into commercial decision-making. Evidence of measurable commitments is emerging but external verification is limited.

governance toolingdeployment safetyrisk underwriting
Why it matters for safety

Insurance is one of the most powerful mechanisms for enforcing safety practices. If AI deployments cannot be insured, enterprises face unlimited liability. If they can be insured, insurers become a de facto safety regulator - demanding evidence of safe practices as a condition of coverage.

Civilizational Risk Awareness

1/3

Generic safety language in the context of risk quantification. The work is highly relevant to safety infrastructure but motivation is market-driven.

Responsible Scaling Policy

None

No RSP. Not a model developer. The equivalent is governance of the underwriting standard itself - ensuring the standard evolves as AI risk landscape changes.

Mission Drift Protection

1/3
  • Mission focused on AI risk quantification
  • No PBC status
  • No structural mechanisms
  • Standards organisation governance structure unclear

Vulnerability Disclosure

None

Not directly applicable - AIUC does not deploy AI systems. Relevant equivalent: responsible handling of risk assessment data that could reveal systemic vulnerabilities in the AI ecosystem.

Safety Reporting

◇ Irregular
AIUC-1 standard updatesirregular

Standard publications are irregular. For a risk quantification organisation, publishing aggregate risk data (anonymised trends, common failure modes) would significantly enhance industry value.

Dual-Use Risk

Not applicable - this company does not develop dual-use AI systems.

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