AI Agent Security for Finance
AI copilots in finance touch sensitive data and regulated decisions. Without controls, you risk leaks, audit failures, and costly incidents.
Key challenges
Prompt injection and tool abuse (fraudulent actions, policy bypass)
Sensitive data leakage (PII/PCI, account details, internal risk data)
Non-compliant outputs and inconsistent policy enforcement
Weak audit evidence for certifications and risk reviews
Long vendor/security reviews slow time-to-production
How Fireraven helps
RedRaven
Automated AI risk assessments + red-teaming aligned to your policies/frameworks; audit-ready reports (gap, coverage, pass rate).
FireGuard
Low-latency input/output guardrails + monitoring; enforce internal rules and compliance continuously.
Applications (use cases)
AML & fraud investigation copilot for analysts
Challenge:
Injection manipulates case decisions; data exfiltration
Fireraven:
RedRaven tests bypasses; FireGuard blocks + logs evidence
Customer support banking chatbot for account servicing
Challenge:
PII leakage; unauthorized disclosures; policy drift
Fireraven:
FireGuard enforces output rules; RedRaven validates resilience
Credit underwriting copilot for risk triage and notes
Challenge:
Non-compliant decision support; unsafe tool access
Fireraven:
FireGuard policy gates; RedRaven stress-tests workflows
KYC onboarding assistant handling documents and user questions
Challenge:
Identity data leakage; prompt attacks during verification
Fireraven:
Guardrails + red-teaming for exfiltration and bypass attempts
Internal policy/Q&A copilot for compliance teams
Challenge:
Confidential policy data exposure; incorrect restricted guidance
Fireraven:
FireGuard controls topics; monitoring + audit trail
Investment research assistant summarizing internal and external sources
Challenge:
Leaking proprietary insights; unsafe prompts requesting secrets
Fireraven:
FireGuard redaction; RedRaven tests hidden extraction patterns