On November 4, 2026, the Office of the Comptroller of the Currency (OCC) issued a supervisory framework (the “SI Supervisory Framework”) to provide a structured approach for OCC bank examiners to assess the use of super intelligence (SI) by banks in normal-course business activities, including credit decisioning, payments, fraud detection, customer service, operations, risk management, and market activities. The OCC notes that the term “super intelligence” refers to the technologies and systems encompassed by the term “artificial intelligence,” citing a recent Executive Order.
According to the OCC, the SI Framework (which was prepared with the assistance of SI) is intended to supplement existing model risk management, governance, technology, compliance, and operational-risk practices, rather than create a stand-alone regulatory regime for SI. The SI Framework consists of six pillars of principal supervisory consideration, and includes a control risk tiering methodology and a technical lexicon as well.
Key Highlights
- The SI Supervisory Framework highlights the following points for banks to be aware of when utilizing SI in normal-course business activities and when considering deployment of SI for new use cases:
- Bank examiners may use the SI Supervisory Framework to identify SI-specific considerations.
- Bank examiners are to tailor their examination of banks’ use of SI to the materiality of the SI use case.
- Bank examiners are to tailor their examinations to bank size, complexity, and risk profile, in proportion with the nature, consequences, autonomy, and complexity of the bank’s SI use cases.
- Bank examiners should not treat SI as a separate and distinct risk category.
- Banks should not be required to define a separate SI risk appetite.
- A bank’s control intensity could increase with the potential consequences of the failure or misuse of an SI agent.
- A bank’s risk classification of SI use cases may be based on potential consequences, transfer of agency, and the degree of human oversight rather than the technical sophistication of the SI used.
- The SI Supervisory Framework does not establish supervisory expectations for banks, establish new regulatory expectations, or set forth enforceable standards or requirements. Nevertheless, the SI Supervisory Framework provides insight into the considerations OCC examiners may apply when evaluating banks’ use of SI, including the consequences of automated decisions, the degree of human oversight, testing, vendor management, and operational resilience.
The SI Supervisory Framework
The six pillars of principal supervisory consideration are as follows:
1. Purpose: Defines the actions that the SI system or agent is permitted to execute.
- Defined Purpose and Permitted Use
- Before deployment and after a material change, a bank may document what an SI system or agent is designed to do, what it is not designed to do, who or what may invoke it, the data and systems it is permitted to access, the actions it could take, and the circumstances that may require human review or suspension.
- The bank’s inventory may link these boundaries to ownership, provenance, autonomy, monitoring, and continuity arrangements.
2. Risk: Assesses the consequences if the output or action of the SI system or agent is not fit for purpose.
- Risk Classification and Criticality Assessment
- A bank may assess each use case before deployment and when material changes occur.
- Relevant factors could include decision consequence, reversibility, customer and financial impact, autonomy, data sensitivity, explainability, provenance, permission scope, and interdependencies.
- Classification may be based on the consequences of failure and transfer of agency.
3. Control: Identifies controls that may prevent unauthorized, inappropriate, or unsafe actions of the SI system or agent.
- Human-in-the-Loop and Human-on-the-Loop Controls
- Human-in-the-loop generally refers to review and approval before an output or action is used or executed.
- Human-on-the-loop generally refers to active monitoring with authority and practical ability to intervene.
- The level of involvement may be calibrated to the potential consequences, autonomy, reversibility, and operating volume of the use case, among other factors.
- Model Risk Management
- Certain Model Risk Management principles may be instructive for development, use, validation, governance, and ongoing monitoring.
- However, the scope, frequency, and independence of SI activities may be adapted to the use case’s potential consequences, rate of change, non-determinism, and reliance on third-party or continuously updated models.
- Data Governance
- Data governance may address data quality, lineage, representativeness, access, retention, and use throughout the SI lifecycle.
- The bank may consider both data provided to the system and new data created through prompts, outputs, embeddings, logs, feedback, or synthetic generation.
- Privacy
- Privacy considerations may include applicable law, permissible use, data minimization, access, retention, deletion, notice, consent, vendor use, and cross-border processing.
- These considerations may be mapped to each use case and revisited when the model, provider, data, or purpose changes.
- Compliance
- SI does not change the bank’s underlying legal obligations and has the potential to facilitate a bank’s compliance with them.
- However, SI’s complexity, opacity, speed, and capacity to act may make it more difficult to identify how a requirement applies, explain an outcome, detect noncompliance, or prevent use outside approved boundaries.
- A bank may consider compliance through design, development, procurement, deployment, monitoring, change management, and retirement.
- Cybersecurity
- Cybersecurity controls may extend to the SI lifecycle and supporting infrastructure, including identity and access management, data and model integrity, secure development, monitoring, incident response, and recovery.
- The breadth of agent permissions and tool access may be treated as part of the attack surface.
4. Oversight: Establishes who monitors the SI system or agent and who is accountable for its use.
- Governance & Accountability
- The board and senior management may establish an SI risk appetite, identify accountable executives and use-case owners, assign responsibilities and receive information on material SI use.
- Governance may be supported by a complete inventory and approval authority at meaningful lifecycle gates.
- Human-in-the-Loop and Human-on-the-Loop Controls, discussed above.
- Performance Monitoring
- Metrics, thresholds, reporting, and escalation may be calibrated to the use case’s potential consequences, autonomy, expected variability, and rate of change.
- Monitoring and in-line real time observability may address both average performance and low-frequency events that could cause material harm.
- Reporting & Transparency
- Internal reporting may be risk-based and may include material use cases, accountable owners, significant changes, control exceptions, incidents, customer remediation, concentrations, and assurance results.
- Various notifications required by laws and regulations, as well as contracts, could be applicable to SI use cases.
5. Resilience: Addresses the ability of the bank to detect, contain, recover from, and remediate SI system or agent failures while continuing critical business processes.
- Operational Resilience
- For more consequential or autonomous use cases, a bank may document and test detection, containment, suspension, continuity, recovery, escalation, and remediation arrangements.
- The approach may address internal SI systems, fallback processes, and external SI agents that interact through bank channels.
- Cybersecurity, as discussed above.
6. Assurance: Provides evidence that SI system or agent controls continue to operate in an effective manner.
- Testing
- The appropriate range, rigor, frequency, and independence of testing may depend on the materiality of the use case, the potential consequences of failure, and the limitations of the SI system.
- Lower materiality uses may warrant limited testing, while consequential or highly autonomous uses may warrant broader testing of both performance and the design and operation of controls throughout the SI lifecycle.
- Documentation & Auditability
- Documentation may be proportionate to the use case and may address purpose, ownership, design, data, providers, versions, prompts, permissions, assumptions, testing, validation, monitoring, decisions, approvals, incidents, and changes.
- Records may support reconstruction of material outputs or actions even when the model cannot produce a rule-based rationale.
- Third-Party & Vendor Risk
- Third-party risk management for SI systems and agentic SI may supplement existing interagency third-party risk management guidance.
- Additional consideration should be given to the following areas where the provider’s SI can affect the bank’s decisions, customers, or data:
- Provider agent visibility;
- SI incidents;
- Liability;
- Change and exit.
- Internal Audit & Independent Challenge
- Audit scope, cadence, skills, access, and reporting may be established through the audit framework and scaled to the bank’s SI use cases.
- Effective challenge may depend on independence from both the group that develops or owns the system and the group that validates or monitors it.
SI/Agent Risk Tiering
The SI Supervisory Framework includes a risk-tiering methodology, which is applied separately to SI models and to agentic systems as risk increases. The goal of the risk-tiering methodology is to provide a graduated control model that uses a light touch for low-risk, low-autonomy use, and a materially heavier touch for anything approaching customer-impacting, irreversible, or highly autonomous action. The risk factors include:
- Decision consequence: Does the system inform a human decision, make a decision directly, or take an action directly (e.g., moving funds, updating a customer record, market interaction)? Direct action carries materially higher risk than decision support.
- Reversibility: Can an erroneous output or action be caught and undone before harm occurs, or is it effectively irreversible once executed (e.g., a payment sent, a disclosure made, an account closed)?
- Customer/financial impact: Magnitude of potential harm to a customer, the markets, or the bank if the system is wrong/makes an error (e.g., a single transaction versus a portfolio-level decision, a low-dollar versus high-dollar threshold).
- Autonomy level: Degree of human involvement in the loop, human-in-the-loop (approves each action), human-on-the-loop (monitors and can intervene), or fully autonomous (acts without a real-time human checkpoint).
- Data sensitivity: Whether the system touches regulated, confidential, or personally identifiable data, and whether inputs or outputs could constitute a privacy or consumer law exposure.
- Explainability: Whether the system’s output can be traced to a rationale that is sufficient to meet legal, regulatory, or customer-disclosure obligations (e.g., adverse action notices).
- Provenance: Whether the system is built in-house, fine-tuned from a third-party base model, or consumed as a fully external vendor service; each origin carries a different visibility and control profile.
These factors combine into a “composite tier”: Tier 1, Critical; Tier 2, High; Tier 3, Moderate; and Tier 4, Low. As an example, an internal productivity tool with no customer or financial data exposure would be in Tier 4, whereas an autonomous, customer-facing payment agent would be in Tier 1, regardless of how well it performs in testing.
Next Steps/Looking Ahead
The OCC emphasizes that the SI Supervisory Framework “should be treated as a living document,” which the OCC intends to update on a regular basis to address developments in SI technology and respond to stakeholder feedback. Although banks are not expected to use the SI Supervisory Framework as a compliance checklist, they should continue to assess SI-related risks within their existing governance and risk management practices as technologies and use cases evolve. The OCC also emphasizes that the agency will continue to take a technology-neutral approach in encouraging bank safety, soundness, and innovation.
Regulatory scrutiny of the use of SI from banking agencies, including on agentic systems and third-party SI providers, will continue evolving. In September, the OCC, Federal Reserve, FDIC, and NCUA proposed updated third-party risk management guidance, while the Federal Reserve separately proposed guidance for traditional community banks. Banks and SI providers should monitor these developments closely, particularly as regulators continue to evaluate the risks associated with autonomous decision-making, vendor accountability, and the use of emerging technologies in financial services.