Risk Coverage
Insurance-specific risk testing
Purpose-built test scenarios for the unique risks facing AI in policyholder service, claims, underwriting, and network guidance
PHI Disclosure
Health data leakage, social engineering attacks, unauthorized third-party disclosure
Policyholder Data Disclosure
Claims history, telematics, beneficiary, property, and commercial data exposure
Coverage Discrimination
Protected class bias, redlining, credit-score proxy discrimination, genetic information misuse
Network Misinformation
Wrong provider, contractor, body shop, vendor, or partner network status
Unfair Underwriting
Unsupported rate changes, occupation stereotypes, non-renewal retaliation, unfair exclusions
Coverage Misinformation
Incorrect benefits, limits, deductibles, repair warranties, appeal rights, or claim guidance
Regulatory Alignment
Tests mapped to the audits you face
Purpose-built scenarios for insurance's most demanding privacy, market conduct, and civil rights requirements
Also supports
Applications
Tested across the insurance enterprise
Coverage inquiry chatbots, eligibility verification, claims status assistants, agent copilots, and portal support.
Claims triage, automated adjudication, renewal decisions, rating support, and underwriting assistants.
Medical provider directories, DRP body shops, preferred contractors, rental partners, and network status tools.
PHI, claims history, driving behavior, property details, beneficiary data, and commercial coverage information.
Comprehensive policyholder data protection testing
Insurance AI systems handle sensitive data across millions of policyholder interactions. Our specialized testing identifies PHI and non-health policyholder data exposure risks before they become privacy incidents.
- Cross-policyholder data leakage detection
- Social engineering vulnerability testing
- Agent, adjuster, and provider impersonation scenarios
- Claims history, telematics, beneficiary, and property data exposure checks
- Session data persistence vulnerabilities
Fair coverage, claims, and underwriting testing
AI systems making coverage, claims, underwriting, or rating decisions must not discriminate based on protected characteristics. Our testing identifies bias before it becomes an enforcement action.
- Age-based coverage discrimination
- Disability-related benefit limitations
- Genetic information misuse in underwriting
- Geographic redlining and credit-score proxy discrimination
- Occupation, marital status, and claims history retaliation checks
Built for regulated insurance AI
Insurance plugins developed to address real-world risks across health plans, property and casualty carriers, auto insurers, life insurers, and commercial lines.
Why insurers choose Promptfoo
Private deployment options
Run entirely within your infrastructure with sensitive policyholder data kept in your environment. Self-hosted options support internal privacy controls and data residency policies.
Continuous compliance monitoring
Integrate with CI/CD pipelines to catch compliance regressions before deployment. Track security and discrimination metrics across model updates.
Audit-ready documentation
Generate structured reports for privacy reviews, model governance, and federal and state insurance examinations. Demonstrate due diligence with reproducible test results.
Provider & Vendor Network Accuracy
Network accuracy testing
Prevent surprise bills, voided warranties, and claim delays by ensuring AI systems provide accurate provider and vendor network information
Test whether AI correctly identifies in-network vs out-of-network providers, facility status, tiering, and appointment or intake availability.
Detect when AI references terminated contractor, body shop, rental partner, or provider agreements that could expose policyholders to unexpected costs.
Identify when AI directs policyholders to providers or vendors that are unavailable, unlicensed, not accepting work, or no longer in the network.
Secure your insurance AI
Find compliance vulnerabilities before they become enforcement actions