An Agentic Finance Assurance Matrix for Authority and Consequence

Sources checked: 10 November 2026. FailSafe Research.

The useful starting point for financial-agent assurance is the authority the system can exercise. A model that drafts a recommendation and an agent that can authorize a transfer require different evidence, even if they use the same underlying model. A test plan should connect the institution's decision boundary to an observable consequence.

What the OCC framework says

The OCC's November 4 examiner framework addresses consequence, transfer of agency and human oversight. It explicitly creates no new supervisory expectations or enforceable standards and does not require banks to use the document for their own assessments. Our matrix is a voluntary engineering aid, not an OCC-prescribed checklist or evidence of regulatory approval.

As an update beyond the brief's November 2–8 coverage, a November 9 speech hosted by the BIS discusses identity, consent, authorization, traceability and consumers' ability to stop or revoke delegated actions. A speech is not a new binding requirement. It helps frame questions about whether an action reflects the authority and intent granted.

Use a matrix with a testable result

Selected rows from the downloadable assessment worksheet

Boundary	Assessment question	Useful evidence
Delegation	Can the agent exceed the approved role?	Test identity, permission decision and synthetic outcome.
Human approval	Does approval bind the final action?	Approved object, final action and policy result.
Revocation	Does already queued work lose authority?	Revocation time and subsequent denials.
Auditability	Can reviewers reconstruct the decision?	Correlated records with sensitive fields controlled.

Download the full CSV worksheet. Each row asks for a configuration, owner, expected boundary, permitted synthetic action and retest record. The worksheet contains no customer findings and does not assign a pass to any bank or product.

What FailSafe assesses

FailSafe scopes AI applications with their identities, APIs and connected tools. Our assessment workflow turns an approved boundary question into a controlled case, captures the observed result and retests the agreed correction. For finance, the scope can include delegated access, approval enforcement and the customer-owned workflow through which an action becomes effective. Access to a production ledger or a third-party payment rail is never implied by the service description.

For example, a fictional payment assistant receives approval for a synthetic transfer to a specified beneficiary. The test observes whether the final operation still matches that approval after an allowed workflow change. A result should identify the checked fields, policy version and actual state transition. A generic model-safety score does not answer that question.

Build a decision record for several owners

Model-risk, operations, payments and security teams may each own part of the boundary. Name the decision owner before testing. Record legitimate controls, blocked cases and inconclusive results. Then assign the correction to the component that actually enforces the action and repeat the case on a recorded deployment.

The AI security assessment guide explains the underlying scope, and the finding example shows how a failure and a retest stay connected. Institution-specific legal or supervisory conclusions remain with the appropriate advisers and authorities.