Sensitive financial data moves through agents daily
Account numbers, credit data, and trading strategies pass through AI-powered workflows constantly, often without dedicated monitoring.
By industry
AI governance for the systems that move money.
Trading, payments, and account data move through agents daily. The blast radius of a leaked position or an unauthorized transaction isn't hypothetical-it's a compliance event, and regulators expect the same rigor you apply to every other regulated system.
Why it matters
The data has outsized consequence
Threat actors target agents specifically
Indirect prompt injection, data exfiltration, and memory poisoning are attack techniques built for exactly this environment.
Regulators expect documented controls
"We use AI responsibly" is no longer a sufficient answer to SEC, FINRA, or examiner questions about AI in investment processes.
What Lineation does
Defensible governance for the systems that can't afford a mistake
Discovery & risk scoring
Every agent touching account, trading, or payment data is inventoried and scored on its data access.
Real-time threat detection
Injection and exfiltration attempts are caught as they happen, not discovered in a post-incident review.
Least-privilege enforcement
Policy is scoped to account, position, and transaction data, enforced at the point of each action.
Automated compliance evidence
Audit-ready reports map continuously to PCI-DSS, SOC 2, and NIST AI RMF.
How it works
Five steps to defensible financial AI
Discover data-touching agents
Every agent touching account, trading, or payment systems is identified.
Score by data access
Risk is scored based on the sensitivity of data and permissions each agent holds.
Enforce least privilege
Policy governs each action at the point it's attempted, not after the fact.
Detect and contain
Injection or exfiltration attempts are flagged and contained in real time.
Generate compliance evidence
Audit-ready reports are produced continuously, not assembled under deadline.
FAQ
Common questions
What are the biggest AI risks specific to financial services?
Employees pasting sensitive data into unsanctioned tools, agents vulnerable to injection and exfiltration, and agents with excessive permissions.
How does this help with SEC, FINRA, or MiFID II data lineage?
Every agent action is captured as a chain from prompt to tool to data to outcome, producing the lineage record examiners ask for.
Can this stop an agent from exporting client data?
Yes-policy scoped to read, write, and export separately means export can be denied by default even when read access is granted.
Does this cover shadow AI usage by employees?
Yes-discovery covers sanctioned and unsanctioned AI tools in active use across the organization.
How does this map to PCI-DSS for cardholder data?
Output redaction and access policy scoped to cardholder data align with PCI-DSS requirements across every AI processing environment.
Can a solo compliance team run this without a security org?
Yes-policy templates and compliance mappings are designed so one engineer can stand up defensible governance in days.
Make your next audit the easy conversation.
Discovery, policy, and evidence-built for the systems that move money.