AI governance in financial services is the control and evidencing of AI use under supervisory obligation: FINRA supervision, model risk management, information barriers and examination response. Smartflow enforces those controls inline on every model call, on-premises, and produces the examination evidence from the records that enforcement generates.
AI Governance Built for Financial Services
Smartflow is the AI governance control plane for banks, broker-dealers, asset managers and financial exchanges. Cryptographic agent identity. Information barrier enforcement. One-click regulatory examination packages for FINRA 3110, FFIEC, model inventory and the EU AI Act.
The supervisory gap agents created
FINRA has published directly on what AI agents do. In January 2026 its Chief Regulatory Operations Officer named six risks: agents acting without human validation, operating beyond their intended scope of authority, multi-step reasoning that resists traceability, unintended disclosure of sensitive data, insufficient domain knowledge, and misaligned reward functions. Four of the six are runtime properties — true or false at the moment the agent acts, not at the moment it was configured.
Model risk guidance moved the other way. SR 26-2, which superseded SR 11-7 in April 2026, places generative and agentic AI outside its scope while stating that the institution's own governance must determine the controls for what it does not cover. Rule 3110, meanwhile, is enforceable and technology-neutral, and it asks a question model risk never asked: did the firm supervise the conduct?
Three Problems Smartflow Solves for Financial Services
1. Agent Identity and Delegated Authority
AI agents are initiating wire transfers, executing trades and accessing customer accounts at financial institutions. AIDA provides the cryptographic identity layer: who authorised the agent, what it was permitted to do, and a complete audit trail of every action it took. That answers the first two risks FINRA named — authority and scope — as a matter of record rather than of policy intent.
2. Information Barrier Enforcement
Every AI assistant deployed across business lines is a potential conduit for material non-public information. Research analysts and trading desks sharing the same LLM endpoint creates regulatory exposure. Smartflow enforces information barriers at the AI gateway using LDAP/AD group identity combined with real-time content classification. MNPI controls with 90-day violation retention. FINRA Rule 3110 attestation reports generated automatically.
3. Regulatory Examination Readiness
A single examination preparation cycle consumes months of consulting time. Smartflow's Regulatory Examination Suite generates complete evidence packages with a single API call: FINRA 3110 supervision package, model inventory, FFIEC IT controls assessment, or EU AI Act high-risk system documentation. 24 hours from request to examination-ready package.
Regulatory Framework Mapping
- FINRA 3110: Supervisory controls, communication review, barrier enforcement, attestation — enforceable and technology-neutral
- Model risk (SR 26-2, superseding SR 11-7 in April 2026): Model inventory, risk classification, validation status, outcomes monitoring. Generative and agentic systems sit outside its scope, which is where the institution's own governance has to answer
- FFIEC: IT risk assessment, access controls, audit trail integrity
- EU AI Act: High-risk system registration, transparency documentation, human oversight
- SOX: Financial reporting AI controls, access authorization, data integrity
Related reading
Agentic AI · Model drift · AI incident response · MITRE ATLAS · AI supervision evidence checklist · AI due diligence in M&A
Put this in the path of your own agents.
Policy enforced inline between your agents and every model and tool they reach, with a record bound to the human who owns it.
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