Insurance

AI agent governance for insurance and reinsurance

Solvency II, NAIC model governance, claims automation: agents handling policyholder PII, actuarial model risk, and real-time adjudication must comply before they go live. Roval gives you the registry, classification, and audit trail your regulators expect.

Agent risk overview
Agent Data access Status
claims-adjudicator Policyholder PII Certified
underwriting-model Financial data Expiring
fraud-detection Claims data Uncertified
fraud-detection accessing claims data without Solvency II certification
The challenge

Insurance model governance wasn't designed for autonomous AI agents

Agents in claims adjudication, underwriting, and fraud detection make real-time decisions that affect policyholders, reserving accuracy, and regulatory capital. Traditional model governance frameworks can't keep pace with autonomous systems that chain LLM calls, access PII, and update pricing models without human review.

Actuarial model validation assumes human-built models with static inputs. AI agents that dynamically adjust pricing or reserving parameters break every assumption in your existing validation framework.

Claims automation agents process policyholder PII (SSNs, health records, policy numbers) at scale. A single misconfigured agent could expose protected data across your entire book of business.

Solvency II requires a complete audit trail for every model influencing capital adequacy. Most insurers can't even enumerate which AI agents touch their reserving or pricing pipelines.

Regulatory frameworks

Regulatory frameworks for insurance

Pre-mapped requirements. Activate a framework and Roval tracks evidence per requirement.

EU
Solvency II solvency-ii

Capital adequacy, risk management, and model governance requirements for AI systems influencing reserves and pricing.

Active
14 requirements Capital adequacy
US
NAIC Model Governance naic-model-governance

State-level insurance regulation for AI and predictive models used in underwriting, rating, and claims.

Active
12 requirements Insurance regulation
Industry
SOC 2 Type II soc2-type-ii

Trust service criteria mapped to agent governance, required by every enterprise customer and reinsurance partner.

Active
18 requirements Annual audit
EU
GDPR gdpr

Data processing, consent management, and right to explanation for AI systems handling policyholder data.

14 requirements Data protection
Industry
ISO 42001 iso-42001

AI management system certification covering risk assessment, lifecycle governance, and responsible AI practices.

31 requirements AIMS certification
US
NIST AI RMF nist-ai-rmf

Voluntary risk management framework for identifying, assessing, and mitigating AI risks across the insurance lifecycle.

22 requirements Risk management
Policies

Pre-built policies for insurance

Start from a template, customize the rules, and activate. Every policy enforces controls on your agents.

Claims automation controls

Monitors agent decisions in claims adjudication: enforces audit logging, approval thresholds, and escalation rules for high-value claims.

Active
12 blocked · 9 sensitive · 5 read-only
Policyholder PII protection

Detects policy numbers, SSNs, and health data in prompts. Blocks sensitive policyholder information from reaching external model APIs.

Active
14 blocked · 11 sensitive · 3 read-only
Underwriting model validation

Enforces documentation and back-testing requirements for AI models used in risk selection, pricing, and policy issuance.

8 blocked · 6 sensitive · 7 read-only
Fraud detection oversight

Requires human oversight for fraud-flagging agents: escalation rules, false-positive review, and decision audit trails.

10 blocked · 7 sensitive · 4 read-only
Actuarial model risk

Validation requirements for AI-driven pricing and reserving models: back-testing, sensitivity analysis, and parameter drift monitoring.

7 blocked · 5 sensitive · 9 read-only
Third-party vendor risk

Controls for agents calling external LLM APIs: data residency checks, vendor approval lists, and cost limits for outsourced model inference.

6 blocked · 4 sensitive · 8 read-only
How it works

Built for the audit that's already scheduled

Full audit trail for regulators

Every state change (registration, classification, certification, policy violation) logged with timestamp, user, and context. Export to PDF for your examiner.

Audit event log
09:14:02
claims-adjudicator Agent registered, owner: j.martinez@acme-ins.com
Registered
09:15:47
claims-adjudicator Risk classified Tier 3, High
Tier 3
10:02:31
underwriting-model Compliance evidence uploaded, Solvency II Art. 44
Evidence
11:38:09
underwriting-model Certification approved, s.okonkwo@acme-ins.com
Certified

Real-time cost attribution

See which agents call which models, how many tokens they consume, and what they cost. Set budget alerts per team, per agent, per model.

Cost attribution, March 2026
Agent Model Tokens Cost
claims-adjudicator gpt-4o 2.1M $1,080
underwriting-model claude-3-5 1.6M $790
policyholder-support gpt-4o-mini 540K $270
fraud-detection-v2 gpt-4o 3.4M $2,040 ↑

Continuous compliance monitoring

Certifications expire. Configurations drift. Owners leave. Roval detects it all within 15 minutes and alerts before your next audit.

Compliance posture
Solv. II
92% Pass
NAIC
100% Pass
SOC 2
85% Review
claims-adjudicator: Art. 44 evidence expires in 6 days
underwriting-model: owner l.nguyen@acme-ins.com departed

See Roval for insurance

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