FINANCIAL SERVICES
AI Security Built For Financial Trust
PurpleSec protects AI systems used across financial services and fintech—securing sensitive data, automated decisions, and critical infrastructure while meeting strict regulatory and operational requirements.
Your AI. Your Controls. Your Confidence.
Secure financial AI—from employee copilots to autonomous agents—without slowing innovation.
Customer-Facing AI, Protected
Stop prompt injection and chatbot abuse—before it becomes fraud or exposure.
PromptShield™ blocks authentication bypass, data extraction, and coercive prompts while keeping customer service fast and available.
Employees Using AI—Safely
Let teams use AI tools without leaking PCI, PII, or sensitive data.
PromptShield™enforces real-time controls so productivity tools don’t become compliance violations or headlines.
Agentic AI, With Guardrails
Enable AI to act—without letting it overstep.
PromptShield™ governs tool use, permissions, and high-risk actions so autonomy scales safely, with human oversight only where it matters.
Proprietary Knowledge, Kept Proprietary
Protect fraud models, risk logic, and strategic data from extraction or misuse.
PromptShield™ prevents reverse-engineering and over-disclosure while still enabling AI copilots to assist employees.
BUILT FOR COMPLIANCE
Support AI Adoption While Meeting Regulatory And Security Standards
Common AI Risk Scenarios In Financial Services
As AI adoption accelerates, financial institutions must manage new risk surfaces while maintaining
compliance, auditability, and customer trust.
Customer Service Chatbots
Manipulated customer service chatbots can bypass authentication, expose internal controls, and enable fraud, leading to regulatory exposure, data loss, and reputational harm.
PCI/PII Leakage LLM Usage
PCI and PII leakage through AI systems drives regulatory exposure, breach notification risk, and loss of control over sensitive data.
Unauthorized Actions In Agentic AI Workflows
Compromised AI systems can execute unauthorized actions that result in financial loss, regulatory violations, audit failure, and loss of customer trust.
Data Extraction on Internal Policies & Procedures
Manipulated customer service chatbots can bypass authentication, expose internal controls, and enable fraud, leading to regulatory exposure, data loss, and reputational harm.
The Shift To Intent-Based AI Security
Static rules and keyword filters fail in financial AI, where attacks can be reworded or hidden across workflows. Risk shows up as coerced chatbot actions, data extraction, or manipulated transactions. Security must understand intent—not just strings.
Frequently Asked Questions
Will This Slow Down Employees Who Legitimately Need To Use AI Tools?
Redaction happens in <100ms. Most employees won’t notice latency. Blocked prompts require rework, but this is the cost of compliance—better than a data breach.
What If An Employee Needs To Analyze Real Customer Data With AI?
Use approved internal AI sandbox with on-premises LLMs (air-gapped, not internet-connected). PromptShield can allowlist these internal tools.
Can Employees Bypass This By Using Personal Devices?
Not if institution enforces “AI tools only on corporate devices” policy. Complement PromptShield™ with network-level blocks (firewall rules blocking OpenAI, Anthropic from personal devices on corporate network).
What About False Positive (e.g., Test Card Number 4111111111111111)?
Configure exemption list for known test PANs. PromptShield can distinguish test data patterns from real customer data via contextual analysis.
Won't Requiring Confirmation For Every Action Slow Down Operations?
PromptShield™ only triggers HITL for high-risk actions (e.g., >$100 refunds, privilege changes). Low-risk routine actions (query account, retrieve case notes) proceed automatically. Properly tuned policies maintain efficiency while ensuring safety.
Can Sophisticated Attackers Bypass These Controls?
Defense-in-depth: Injection detection catches manipulation attempts, parameter validation enforces business logic, rate limiting blocks bulk abuse, and HITL provides final human judgment. Bypassing all layers simultaneously is extremely difficult.
What If The AI Misinterprets A Legitimate Request As An Injection Attempt?
False positive handling: If AI blocks a legitimate action, human operator can:
- Review the block reason.
- Override if justified (logged for audit).
- Report false positive to tune detection rules.
- Target: <2% false positive rate (1-2 per 100 actions).
How Does This Work With 3rd Party AI Platforms (OpenAI Assistance, Microsoft Copilot)?
API Gateway mode: PromptShield™ sits between the AI platform and your internal systems. The AI makes function calls to PromptShield’s™ API, which enforces policies before proxying allowed actions to actual banking systems.
Will This Frustrate Employees Who Need Detailed Policy Guidance?
Properly tuned tiers allow legitimate detailed access for authorized roles. Fraud analysts CAN get specific fraud playbook details—they just can’t export the entire knowledge base or query outside their domain. False positive rate <5% means 95%+ of legitimate queries work normally.
What If An Employee Has A Legitimate Need To Access Cross-Domain Knowledge?
Exception request workflow: Employee submits justification → Manager approves → Temporary access granted for specific session → Logged for audit. Example: Fraud analyst working on cross-functional project with Credit Risk can request temporary underwriting policy access.
How Do We Balance Security With Usability?
Start permissive (Tier 1-2 widely accessible), tighten based on observed attack patterns. The goal is not to block all detailed information—it’s to prevent bulk extraction and unauthorized cross-domain access.
Can This Prevent A Determined Insider With Months Of Acces?
No single control is perfect. PromptShield™ raises the bar (attacker needs many sessions, risks triggering anomaly detection, leaves extensive audit trail). Combine with other insider threat controls: behavioral analytics, DLP, periodic access reviews.