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Banks should monitor third-party AI tools through the same risk-based oversight they apply to other third-party relationships: inventory each use, assess its potential harm, investigate the provider, secure the information and access needed for oversight, monitor performance and controls, escalate deficiencies, and plan for transition or exit. The bank remains responsible for its activities even when an outside provider performs them. AI does not change that accountability; it makes it especially important to understand what the tool does, what information it handles, and how changes to the service could affect customers or operations.
What does monitoring a third-party AI tool involve?
Monitoring is not a one-time vendor review or a check that ends when a contract is signed. It is oversight throughout the relationship: before selection, during use, whenever material conditions change, and when the bank is considering restricting or ending the arrangement. The Federal Reserve, FDIC, and OCC’s 2023 Interagency Guidance on Third-Party Relationships describes this lifecycle and makes clear that outsourcing an activity does not reduce the bank’s responsibility to meet applicable requirements.
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A “third-party relationship” is not limited to a particular contract format. The agencies’ guidance addresses arrangements in which a provider performs services, activities, or functions for a banking organization. A bank therefore needs to consider AI embedded in a larger service as well as a separately purchased tool, and should look beyond the name of the product to the activity it supports.
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For AI, a useful monitoring program connects four questions: What is the tool being used to do? What could go wrong for customers, the bank, or its compliance obligations? What evidence can the bank obtain about the provider and service? And what will the bank do if the evidence, performance, or risk changes? The AI-specific examples in this article—such as checking for model, data-use, or subcontractor changes—are practical ways to apply the general third-party guidance, not a verbatim regulatory checklist.
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How should a bank decide how much oversight is needed?
Start with the actual use and the consequences of failure, rather than assuming every AI service has the same risk. The 2023 interagency guidance calls for oversight tailored to the bank’s size, complexity, risk profile, and specific relationship. It calls for more comprehensive oversight when a relationship could significantly affect customers, operations, or the bank’s financial condition, or otherwise create significant risk.
Assess the activity, not just the technology
Ask what the tool does in the bank’s process and how much human review occurs before its output affects a decision or action. A tool used for an internal draft may have a different impact from one whose output is used in customer communications, operational workflows, or a process subject to regulatory obligations. These examples are prompts for the bank’s own risk assessment, not a regulator-issued classification of AI use cases.
Consider plausible failures and dependencies
- What could happen if the tool is unavailable, produces inaccurate or unsuitable output, or changes in a way the bank did not anticipate?
- Could sensitive information be disclosed, retained, or used in a way inconsistent with the bank’s requirements or commitments?
- Would the bank be able to detect a problem, review affected work, and continue the activity without the provider?
- Does the use affect customers, important operations, compliance obligations, or a critical dependency on another service?
- Can the bank obtain enough information to oversee the provider, or would limits on disclosure leave a material blind spot?
Document the reasoning behind the risk tier and revisit it when the tool, provider, data, connected systems, customer impact, or business purpose changes. A tool’s original assessment may no longer describe its current use.
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An inventory gives the bank a practical way to identify its relationships, establish ownership, and find uses that may need more intensive attention. The interagency guidance supports maintaining an inventory and identifying relationships that support higher-risk activities. For an AI-enabled service, record enough detail to connect the vendor relationship to the bank activity and the information at stake.
- Provider and service: the provider, tool or service name, relevant version or service identifier when available, and the bank business owner.
- Use and impact: the business purpose, process supported, whether outputs reach or affect customers, and whether the service supports a higher-risk or critical activity.
- Information: the types of data handled, including sensitive information, and the bank’s understanding of how the provider handles it.
- Connections: connected bank systems, users or teams with access, and downstream providers or subcontractors relevant to delivery.
- Oversight record: the risk assessment, due-diligence evidence, contract terms, monitoring reports, incidents, findings, remediation plans, and decisions about renewal, restriction, transition, or termination.
These inventory fields are a practical implementation of the guidance’s relationship inventory and recordkeeping principles; they are not a prescribed regulatory form. The bank should use a format that lets managers locate the accountable owner, understand the use, and retrieve the supporting evidence.
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What should banks ask AI vendors before choosing a tool?
Due diligence should be specific to the activity the provider will perform. The 2023 guidance discusses evaluating a provider’s ability to perform, its control environment, legal and compliance capacity, information security, financial and operational resilience, subcontractors, and limits on information it will disclose. A bank should determine whether it can obtain evidence appropriate to the relationship’s risk—not merely collect generic assurances.
Questions about the provider and its controls
- What capabilities and resources support the service, and what controls govern its operation?
- What information-security and operational-resilience evidence can the provider share, and how current is it?
- Which subcontractors are involved in providing the service, and what oversight applies to them?
- What information will the provider not disclose, and why? Can the bank obtain alternate evidence or impose additional controls if important details are unavailable?
- How will the provider notify the bank of relevant incidents, service interruptions, or changes?
Questions specific to the AI service
To make general due diligence useful for an AI-enabled relationship, ask how the service uses the bank’s information, what service or model changes might affect the bank’s use, and what evidence is available to assess performance in the bank’s context. Clarify which aspects of the provider’s process the bank can observe or test and which remain outside the bank’s visibility. These are implementation questions derived from the general oversight framework; the sources do not establish a universal set of mandatory AI-vendor questions.
If information needed for oversight is unavailable, record the limitation and assess its significance. Depending on the risk, the bank may seek alternate evidence, add controls or monitoring, limit the use, or select another provider. A missing answer is not automatically proof of a failure, but it can make the relationship harder to oversee.
How can contract terms make monitoring possible?
Monitoring depends partly on what the bank can learn and what it can do when a concern arises. The interagency guidance treats contract negotiation as part of third-party risk management and discusses oversight, access, compliance, subcontracting, data, and continuity. The precise terms will depend on the use, applicable law, the institution’s policies, and its negotiating position; the guidance does not prescribe a universal AI contract clause.
For the particular relationship, consider whether the contract supports appropriate access to information, audit or testing rights, notice of material service changes and incidents, remediation expectations, controls over relevant subcontractors, data-handling expectations, and transition assistance. The aim is not to collect clauses as a checklist detached from risk: the bank needs terms that let it obtain meaningful evidence, investigate issues, protect its interests, and maintain or move the activity if necessary.
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Before signing, compare the oversight the bank expects to perform with the access and cooperation the provider has agreed to supply. If a high-impact use depends on information or testing the provider will not permit, resolve that mismatch through alternate evidence, additional safeguards, a narrower use, or a different arrangement.
What should ongoing AI vendor monitoring include?
The agencies say ongoing monitoring may be periodic or continuous, depending on the relationship’s risk and complexity. Their examples include reviewing provider reports, meeting with the provider, testing the bank’s own controls, and, in some circumstances based on risk, directly testing the provider’s controls. They do not prescribe one monitoring cadence for every bank or AI service. The bank should set and explain a cadence that fits the assessed risk and its ability to detect harm in time.
Review the service and evidence
Track relevant service performance and control evidence against what the bank needs for the activity. Review provider reports and meet with the provider as appropriate. For AI, practical questions include whether the provider changed the model or service, its data use or retention, access controls, subcontractors, or performance characteristics relevant to the bank’s use. These are monitoring prompts based on the general guidance, rather than an enumerated supervisory checklist.
Test the bank’s own controls
Provider oversight is only one side of the relationship. Test the bank’s controls around access, use, review, and handling of the service in the actual workflow. Determine whether employees follow the bank’s process, whether required human checks occur, and whether the bank can identify and respond to problems. The interagency guidance specifically includes testing the banking organization’s controls as an ongoing-monitoring activity.
Consider direct provider testing when risk warrants it
Depending on risk and the arrangement, consider whether the bank needs direct testing of provider controls. Whether that is feasible may depend on agreed access and the provider’s cooperation. Where direct testing is not available, the bank should understand what other evidence it can obtain and whether that evidence is adequate for the exposure.
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Monitoring should also consider provider viability and operational resilience, relevant audit findings, security events, service interruptions, data loss, and compliance lapses. The guidance identifies these kinds of developments as warning signs requiring attention; their significance depends on the circumstances and the relationship.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How should a bank respond to incidents or deficiencies?
Monitoring only helps if significant issues reach people who can act. The interagency guidance identifies material or repeat audit findings, deterioration in a provider’s financial condition, security breaches, data loss, service interruptions, and compliance lapses as examples of warning signs. A bank should respond to significant problems, oversee remediation, and determine whether the relationship continues to meet its expectations and risk appetite.
For each material issue, the bank should establish the facts, assess effects on customers and operations, decide whether the service needs to be restricted or suspended, assign a remediation owner and deadline, and retain evidence of the decision and follow-up. AI-related change questions may include whether the service, data use or retention, access controls, or subcontractors changed; treat them as practical inquiry points, not automatic grounds for a regulatory conclusion.
Set escalation routes and decision authority before an incident occurs. A useful process identifies who receives alerts, what information is needed for triage, who can require corrective action, and who can approve restricting use, switching providers, or exiting. The appropriate response depends on the event, risk, contract, and applicable obligations; a single response should not be assumed for every incident.
How should banks document and report AI vendor risk?
Documentation makes oversight auditable and helps decision-makers see whether identified risks are being managed. The interagency guidance discusses board oversight, management accountability, periodic reporting, escalation, independent review, and records that include inventories, assessments, contracts, monitoring reports, remediation plans, disruptions, and security events.
Keep a traceable record of the bank’s assessment, the evidence it relied on, known information gaps, monitoring results, incidents and findings, corrective actions, and decisions to continue, change, or end the relationship. Reports to management and the board or an appropriate committee should be proportionate to the risk and help them understand material dependencies, open issues, and remediation status. Preserve enough context to explain why the bank selected its oversight approach and how it reassessed the relationship when conditions changed.
What do the 2026 U.S. guidance updates mean for AI oversight?
The current regulatory posture needs careful description. The 2023 third-party guidance remains the lifecycle framework described above. In April 2026, the Federal Reserve, OCC, and FDIC issued revised Supervisory Guidance on Model Risk Management. It addresses vendor and third-party products, including validation, monitoring, governance, and controls, but it expressly excludes generative and agentic AI models. It is not a dedicated supervisory rule for generative AI.
The agencies describe the revised model-risk guidance as non-prescriptive and not enforceable. They expect it to be most useful for banks with more than $30 billion in assets, while noting it may also be relevant to smaller institutions with significant model-risk exposure. The $30 billion figure is an applicability indicator stated by the agencies, not a statistical threshold that by itself determines the right controls for every bank.
For systems outside its scope, including generative and agentic AI models, the revised model-risk guidance says governance and risk-management practices should guide controls. That does not mean those systems have no relevant oversight: the general third-party relationship framework still informs how a bank manages an outside provider.
Separately, on September 11, 2026, the OCC issued a proposal to revise and replace existing third-party risk guidance. The proposed guidance emphasizes assessing risk for each relationship and tailoring practices, rather than treating every relationship as inherently high risk. It remains proposed guidance, not a final requirement. The OCC says it will not set enforceable standards or prescriptive requirements; that status does not exempt banks from applicable laws or rules.
The OCC also says the agencies plan a future request for information on model risk management and banks’ use of AI, including generative and agentic AI. The reviewed official sources do not establish the contents of that future request, so banks should not treat it as a published set of new requirements.
A practical lifecycle checklist
- Inventory the relationship: identify the provider, service, owner, purpose, data, connected systems, customer impact, downstream providers, and support for higher-risk activities.
- Set a risk-based oversight level: assess potential customer, operational, compliance, and financial harm, along with the bank’s ability to oversee the relationship.
- Perform activity-specific due diligence: evaluate provider capability, controls, security, resilience, compliance capacity, subcontractors, and information limits.
- Make monitoring workable in the contract: address appropriate access and evidence, testing, change and incident notice, remediation, subcontractors, data handling, and continuity.
- Monitor throughout the relationship: set risk-appropriate periodic or continuous oversight, review reports and changes, test bank controls, and consider provider-control testing when warranted.
- Escalate and track issues: assign owners, establish remediation expectations, document decisions, and consider restricting, replacing, transitioning, or terminating the service when warranted.
- Report and reassess: give appropriate management and board-level visibility, and reassess when the provider, tool, data, use, or impact changes.
This checklist is a practical synthesis of the interagency lifecycle and monitoring principles, not an agency-issued scoring tool. Its purpose is to keep oversight connected to the actual use, the evidence the bank can obtain, and the consequences of a failure.
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