AI agents for financial services compliance
AI agents for financial services compliance, with evidence not attestations
GLBA safeguards, PCI DSS need-to-know, NYDFS Part 500, SR 11-7 — an AI agent touching customer NPI must satisfy the same access, logging, and retention requirements as a human employee, with different evidentiary standards per regulator. Most agent stacks can't produce that evidence.
DataShield tokenizes NPI at ingest, scopes every governed tool call to agent identity with mid-session revocation, and seals each call into a hash chain a regulator — or a skeptical engineer — can verify.
PCI DSS AI chatbot risk, GLBA AI data protection, and audit gaps — mapped to mechanisms
Cardholder data in agent context
PCI DSS restricts access to cardholder data by need-to-know with unique identification. DataShield keeps PANs and account identifiers out of the agent query path entirely: fields are classified and tokenized at ingest with deterministic, join-preserving tokens, so a support chatbot resolves the account without ever holding the number. See Ontology.
Agents outliving their authority
A revoked analyst keeps working through a still-running agent session — unless authority is re-checked. Every governed tool call passes token scope ceiling, authority tier, and a mid-session revocation re-check before metered dispatch. Break-glass emergency access auto-revokes and can't be quietly deleted from the log. See Auth.
Logs that wouldn't survive an examiner
The GLBA Safeguards Rule amendments added explicit access-control, MFA, and audit-log retention requirements. Mutable SIEM logs prove little. DataShield's SHA-256 hash chain with Ed25519-signed checkpoints lets verification distinguish tampering, insertion, deletion, and truncation — run it yourself.
GLBA Safeguards Rule and AI agents: NPI protection you can demonstrate
GLBA requires protecting customer NPI against unauthorized access; the Safeguards Rule amendments made encryption, access controls, and audit-log retention explicit. An agent is an access path like any other — 97% of organizations breached through AI apps lacked AI access controls (IBM 2025), and shadow AI adds $670K to the average breach (IBM Cost of a Data Breach 2025).
EU regulators point the same direction: EDPB Opinion 28/2024 names pseudonymization as a GDPR mitigation — the reversible-tokenization pattern DataShield implements, as opposed to one-way redaction that destroys data for every downstream use.
Model risk and examiners. SR 11-7-style scrutiny asks what data the model saw and under whose authority. Per-tool-call metering attributed to agent identity answers that question with a record, not a diagram. Bring your IdP — Entra or Okta tells you who the agent is; DataShield proves what it did was allowed. Read the architecture and security posture.
Financial services AI governance: buyer questions
Does DataShield keep our AI chatbot inside PCI DSS scope boundaries?
It shrinks what the chatbot can see. Cardholder data is tokenized at ingest, so the agent query path carries tokens, not PANs. Scope determination is your QSA's call, but need-to-know access and unique identification are enforced per governed tool call, with attributed metering as evidence.
Can we revoke an agent's access mid-session?
Yes. Authority is re-checked on every governed tool call, so a revocation or suspension takes effect mid-session — the context is downgraded rather than waiting for a token to expire. This is the direct answer to the Asana-style 34-day exposure window.
How does this satisfy audit-log retention requirements?
Logs are hash-chained with signed, chained checkpoints, so retained logs are tamper-evident, not just retained. GDPR-style erasure works by crypto-shredding key material without breaking the chain. Verification is public — see /verify.
Is this a real-time prompt firewall?
No. DataShield is not an inline traffic interceptor. Data is tokenized at ingest, per dataset; agents query tokenized data over MCP; detokenization is a privileged, audited vault operation. Governance by architecture, not by regex on prompts.
NPI tokenized at ingest, every agent call metered and sealed — self-hosted or in your VPC, with your keys.
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