Deploy Insurance AI Faster With Audit-Ready Governance

RiskAI dynamically maps use cases to the EU AI Act, ISO 23894, NIST AI RMF, and EIOPA-guided controls, auto-generating evidence (model cards, tests, approvals) and ensuring robust AI risk management. Reviews are reduced from weeks to days without sacrificing control.

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

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
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.

Insurance Regulators

EIOPA guidance, NAIC AI Principles

Internal Governance requirements

Risk tiers, Risk identification, assessment, treatment, remediation, human oversight, post-market monitoring.

See Mapping (Sample)

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
3rd Line (Internal Audit)
Read-only workspace and exportable audit 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.

Ready to De-Risk Insurance AI?

Get a sample audit binder or a regulatory mapping to evaluate in your governance committee.

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