Deploy Insurance AI Faster With Audit-Ready Governance & Liability Readiness

RiskAI dynamically maps use cases to the EU AI Act, ISO 23894, NIST AI RMF, and EIOPA Opinion (2025)–aligned controls, autogenerating evidence (model cards, tests, approvals) and ensuring robust AI risk management. Reviews are reduced from weeks to days without sacrificing control and your program becomes underwriting‑ready for AI liability.

Insurance AI governance dashboard with controls and approvals
See Control Evidence (Sample) Book a 30‑min Risk Review

Built for Insurance AI

RiskAI ships with governance hooks for the highest-exposure insurance use cases.

  • Claims automation: fraud detection, severity prediction, straight-through processing
  • Underwriting & pricing: risk scoring, rate filings, new product risk
  • Customer engagement: assist, recommendations, renewals
  • Loss prevention: IoT/telematics analytics, catastrophe modelling
  • Reserving & actuarial: forecast accuracy, model validation evidence
  • GenAI ops: assistants with guardrails, PII controls, response logging

What RiskAI Guarantees for the 2nd Line

  • Pre-mapped control library to EU AI Act obligations (risk mgmt, data, transparency, human oversight, PMM)
  • Model Register with ownership, risk tier, lineage, approvals
  • Evidence Builder: model cards, test plans, sign-offs, immutable audit log
  • Continuous Monitoring: drift, bias, data quality, incidents & escalations
  • Three Lines of Defense workflows with gated approvals
  • Underwriting‑ready exports for cyber/E&O/AI liability (controls, incidents, response playbooks)
  • EIOPA Opinion alignment pack: cross‑reference to fairness, data governance, explainability, human oversight, robustness & cybersecurity controls

CRO Outcome Snapshot

12 → 4 weeks
Regulatory submission cycle
0 major findings
Post-deployment audit
50%
Manual evidence reduction
+13 weeks
Faster fraud model launch
1 export
Underwriting pack for insurers
How we measure these

Regulatory Coverage

EU AI Act

Risk tiers, RMF, transparency, human oversight, post-market monitoring.

ISO 23894

AI risk management alignment & templates included.

NIST AI RMF

Govern–Map–Measure–Manage mapped to controls.

EIOPA Opinion (2025)

Fairness & ethics, data governance, documentation, transparency & explainability, human oversight, accuracy/robustness & cybersecurity.

Internal Governance requirements

Risk tiers, risk identification, assessment, treatment, remediation, human oversight, PMM.

See Mapping (Sample)

EIOPA Opinion Alignment (Highlights)

  • Proportional, risk-based approach: impact assessment considering data sensitivity, customer reach (incl. vulnerable customers), autonomy, and consumer-facing use.
  • Roles & responsibilities: clearly defined ownership; third-party accountability with due diligence, SLAs, audits, and monitoring.
  • Fairness & ethics: customer‑centric policies and training; address discriminatory outcomes.
  • Data governance: complete, accurate, appropriate data; document limitations; remove unlawful proxies.
  • Transparency & explainability: meaningful explanations and decision lineage where feasible; compensating controls where not.
  • Human oversight: defined interventions, escalation paths, and approval checkpoints.
  • Accuracy, robustness & cybersecurity: pre‑deployment testing and ongoing monitoring.
  • Monitoring & redress: fairness/non‑discrimination metrics, audits, and complaint/redress workflows.
View EIOPA Opinion

Transfer AI Risk: Enable Insurance & Claims Defense

  • Underwriting evidence: export control maps, testing, approvals, incident history, and playbooks as a single pack.
  • Coverage alignment: map exposures to AI liability.
  • Claims defense support: immutable logs, decisions lineage, human‑in‑the‑loop attestations.
  • Reasonable‑misuse design: document guardrails and monitoring that address foreseeable misuse.
  • Change & updates duty: versioned risk re‑assessments on each material model change.
  • Bias & robustness dossiers: archived tests with thresholds and sign‑offs for audit and litigation.
  • Vendor ecosystem: third‑party model & data due diligence captured in the register.
  • Breach & incident playbooks: roles, SLAs, notifications, and after‑action reviews linked to models.
  • Customer redress: complaint handling and remediation workflows linked to model versions.

Note: RiskAI is not an insurer and does not provide legal advice. We provide governance tooling and documentation that may support your underwriting and claims processes.

Three Lines of Defense, Operationalized

1st Line (Actuarial/Model Owners)
Guided intake, auto-controls, documentation generator
2nd Line (Risk & Compliance)
Live dashboards, gaps by framework, overdue actions, underwriting artifacts
3rd Line (Internal Audit)
Read-only workspace and exportable audit/underwriting binder

How It Runs Day-to-Day

  • Approval gates (Design → Validation → Pre-Prod → Prod)
  • Escalations with SLAs, severity levels, on-call
  • Change management with versioned evidence & rollbacks
  • AI Risk lifecycle Risk (Identification → Assessment → Measurement → Remediation/Treatment)

FAQs for Insurance CROs

How do you prevent AI sprawl and shadow models?

Enforced Model Register, SSO/RBAC, mandatory gates, API discovery and policy checks.

What happens if a model fails in production?

Incident runbooks, automatic rollback, communications workflow, RCA & corrective actions captured and linked to the model version.

How is fairness/robustness evidenced?

Built-in test batteries with thresholds, approvals, archived reports, and lineage bound to datasets and code commits.

Data residency and subprocessors?

EU/US regions, encryption in transit/at rest, DPA available; current subprocessor list on request.

Who owns model decisions?

You do. RiskAI provides governance tooling and auditable evidence; decision ownership remains with the insurer.

Can RiskAI help us obtain or improve insurance coverage?

We provide underwriting ready exports (controls, incidents, playbooks) and evidence that demonstrate risk maturity to insurers. We do not guarantee coverage decisions or premium outcomes.

How does documentation support claims defense?

Immutable audit logs, model lineage, human oversight attestations, and archived test results help show due care and compliance with internal and regulatory standards.

Are you aligned with EIOPA's Opinion on AI governance?

Yes. Our control library and evidence map directly to the EIOPA Opinion (2025) areas such as fairness & ethics, data governance, documentation, transparency & explainability, human oversight, and accuracy/robustness/cybersecurity, plus roles/responsibilities, third‑party due diligence, monitoring and redress. We provide an EIOPA mapping export for audits.

Ready to De‑Risk Insurance AI?

Get a sample audit binder or an underwriting readiness pack for your governance committee.

View Audit Binder (Sample) Book Risk & Controls Deep Dive