AI Agent Security for Insurance
Insurance copilots impact claims and underwriting. Weak safeguards create privacy risk, compliance exposure, and expensive production mistakes.
Key challenges
Claimant PII leakage and unauthorized disclosures
Prompt injection affecting claim outcomes or fraud workflows
Policy drift across regions/products and evolving compliance requirements
Lack of repeatable evidence for audits and vendor reviews
High cost to build and maintain internal guardrails
How Fireraven helps
RedRaven
Tailored AI pentests mapped to your policies/regulatory obligations; pass rates + coverage + gap report.
FireGuard
Real-time enforcement for inputs/outputs; monitoring, alerts, audit evidence.
Applications (use cases)
Claims triage copilot for adjusters and intake
Challenge:
PII exposure; policy misrouting; injection attempts
Fireraven:
FireGuard blocks/redacts; RedRaven tests edge-case bypasses
Underwriting assistant for risk summaries and pricing support
Challenge:
Unapproved factors; policy violations; unsafe data requests
Fireraven:
FireGuard rules; RedRaven validates coverage by policy
Fraud investigation copilot for suspicious pattern analysis
Challenge:
Data exfiltration; injected prompts biasing investigations
Fireraven:
RedRaven adversarial tests; FireGuard enforcement + logs
Customer self-service chatbot for coverage and claims status
Challenge:
Leaking account info; disallowed advice; policy drift
Fireraven:
FireGuard compliance filters; monitoring
Agent/broker support copilot for product guidance
Challenge:
Non-compliant recommendations; restricted disclosures
Fireraven:
FireGuard policy guardrails; RedRaven tests evasion prompts
Internal knowledge assistant for procedures and compliance playbooks
Challenge:
Confidential SOP leakage; unsafe instructions
Fireraven:
FireGuard topic restrictions + audit trail