Framework · v1.0
The AI Finance Governance Framework
A vendor-neutral standard for trusting AI with money. Eight control domains you can use to evaluate any AI finance tool, including ours, write an internal AI policy, or prepare for an audit.
Jay Manwani, Chief Technology OfficerVersion 1.0 · August 4, 2026
“AI may recommend anything. It may only execute what policy permits. And every consequential or irreversible action requires a named human’s approval, with proof.”
The one principle the eight domains operationalize.
Every finance leader now asks the same question: how do I trust AI to touch the books and the money?There is no shared answer yet, so here is one. Not marketing; a governance model. A finance function is safe to automate to the degree it enforces the eight domains below, not merely describes them.
The eight control domains
1
Bounded Authority
AI operates only within explicitly granted, least-privilege limits.
- Requirement
- Every agent has a declared scope (what it may read, draft, and do) and a hard ceiling it cannot exceed.
- How to verify
- “What is this agent NOT allowed to do, and what technically enforces that?”
Anti-pattern: An agent holding broad API keys with no action-level limits.
2
Human Approval on Consequential Actions
Irreversible or material actions require a named human; low-risk reads flow freely.
- Requirement
- Money movement, filings, and irreversible writes are draft-first and confirmed by a specific person. Reversible, low-risk actions may proceed automatically.
- How to verify
- “Who approved this, by name, and could they have declined before it happened?”
Anti-pattern: "Human in the loop" that is really a notification after the fact.
3
Policy Before Action
Every action is checked against policy BEFORE it executes, not flagged after.
- Requirement
- A decision point evaluates each proposed action against explicit rules (limits, sanctions, budget, authority) and returns allow / deny / needs-approval before anything happens.
- How to verify
- “Is the check a gate, or a report?”
Anti-pattern: Discovering the out-of-policy payment on next month’s statement.
4
Explainability
Every decision states its inputs, the policy applied, and its rationale, in human terms.
- Requirement
- Each action carries a plain-language "why": what data it used, which rule applied, what it concluded.
- How to verify
- “Can a controller understand why the AI did that without reading raw logs?”
Anti-pattern: A confidence score with no reasons.
5
Segregation of Duties
Whoever, or whatever, initiates an action cannot also approve it.
- Requirement
- The AI that proposes an action is not the authority that approves it. Initiation and approval are separated end to end.
- How to verify
- “Can one actor both create and approve the same transaction?”
Anti-pattern: An agent that books and approves its own journal entry.
6
Evidence by Default
Every action and approval is recorded to a tamper-evident, verifiable trail as a byproduct of operation.
- Requirement
- An append-only, tamper-evident (e.g. hash-chained) log of what happened, on what inputs, under which policy, approved by whom: exportable and independently verifiable.
- How to verify
- “Can you prove, on request, that a control held all period, without assembling evidence after the fact?”
Anti-pattern: Screenshots gathered the week before an audit.
7
Confidence & Escalation
Low-confidence or unfamiliar cases escalate to a human instead of guessing.
- Requirement
- The system knows when it is unsure and routes those cases to a person, rather than acting at low confidence.
- How to verify
- “What happens when the AI is not sure?”
Anti-pattern: The model always acts, regardless of confidence.
8
Reversibility & Containment
Every automated action is reversible or contained, with a defined undo / stop path.
- Requirement
- Automated actions can be rolled back, or are bounded (simulate / cap) until trust is established. A kill switch exists.
- How to verify
- “If the AI is wrong at 2am, what is the blast radius, and how do you stop it?”
Anti-pattern: Irreversible automated actions with no rollback.
How to use it
Score any AI finance tool, yours or a competitor’s, against the eight domains. A tool is trustworthy to the degree it enforces them, not merely mentions them. Use it three ways:
- Vendor evaluation: a scorecard for any "AI finance" claim
- Internal AI policy: the controls your own agents must meet
- Audit prep: the questions your auditor will ask about AI
Published under CC BY 4.0 : adopt it, adapt it, cite it. “The AI Finance Governance Framework” is a trademark of Endless Moments LLC.
How Fintra maps to the framework
We wrote this standard and hold ourselves to it. Here is our own conformance, stated plainly, including the two domains Fintra meets only in part.
| Domain | Fintra today | Notes |
|---|---|---|
| Bounded Authority | Live | Agents call a governance decision point bounded by delegated-authority limits. |
| Human Approval | Live | A payment above your approval threshold, a vendor bank change and a role change wait for a named, independent approver; the AI copilot’s writes wait for the signed-in person to confirm them. |
| Policy Before Action | Live | Agent Fence decides before a bill payment is recorded, an ACH file is written, a vendor’s bank details change or a role changes, and the pay run screens each payee against the OFAC SDN list. |
| Explainability | Live | Each decision returns a structured, plain-language rationale. |
| Segregation of Duties | Live | Initiation and approval are separated (SOX-aligned control). |
| Evidence by Default | Live | Hash-chained, tamper-evident evidence ledger with a verify endpoint. |
| Confidence & Escalation | Partial | Consequential actions route to a named approver by rule; escalation does not read a model’s confidence score. |
| Reversibility & Containment | Partial | Fintra moves no money itself, so a sent payment is recalled through your bank; Fintra records the payment and the decision, and undoes neither on its own. |
Live = enforced in production today.Partial = in place for consequential actions; the note says what is not covered.
Frequently asked questions
Is this framework specific to Fintra?
No. It is deliberately vendor-neutral: a checklist you can use to evaluate any AI finance tool, write your own internal AI policy, or prepare for an audit. Fintra authored it and holds itself to it, but the framework stands on its own.
Can I use it without buying Fintra?
Yes. The framework is published under a Creative Commons Attribution license: adopt it, adapt it, and cite it freely, whatever software you run.
How is this different from a "guardrail" feature?
A guardrail is one control. Governance is the whole model: authority, approval, policy-before-action, explainability, separation of duties, evidence, escalation, and reversibility, working together and enforced, not merely described.
How is it different from SOC 2?
SOC 2 attests that controls existed over a period. This framework governs how AI ACTS in real time: whether a money-moving action is checked and approved before it happens, and evidenced after. They are complementary: one is periodic attestation, the other is runtime enforcement.
Bring one workflow to a 15-minute demo.
Tell us which job you want to see, and we will run it in Fintra while you watch.