CFO+AI
Controls

How AI stays safe in a regulated finance function

Built for auditors. Five control layers ship with every engagement — not bolted on after. This is what lets a PE firm, a portfolio company CFO, and counsel say yes without a separate risk review.

01
AI never executes

Generates, recommends, flags, drafts. Never approves, executes, transfers, or posts. The human is always the approver. Stated explicitly in every SOW.

02
Validation gates

Every output passes deterministic checks before a human sees it: cross-reference against system-of-record, completeness, range vs historical norms, format. Flagged → human review. Clean → through.

03
Immutable audit trail

Every output logged with timestamp, model & prompt version, input hash, validation result, reviewer, and action (approved/edited/rejected). Queryable, immutable. This is the SOX evidence when the auditor asks “how was this number produced?”

04
Segregation of duties

Configurer ≠ approver. Prompt changes require peer review and approval. Model version updates follow change management: test → stage → approve → deploy.

05
Drift monitoring

Weekly automated holdout check: current prompts vs baseline on known-good documents. Accuracy drop >5% triggers investigation. Provider version change auto-flags re-validation.

What this covers

  • • Finance, accounting and IR workflows: board books, investor updates, lender packages, close & variance narratives, contract abstraction, AP coding
  • • SOX-relevant boundary: AI never touches journal entry approval, reconciliation sign-off, or disbursement authorization — deterministic rules only; AI may flag anomalies for review
  • • Board/IR content: AI drafts, human edits and approves, version history preserved

Risk-tiered model strategy

RiskExamplesApproach
LowInvoice coding suggestions, first-draft varianceFrontier model, human-reviewed
MediumContract extraction, covenant monitoringFrontier + validation layer
HighBoard narrative, investor commsFrontier + human-in-loop + approval workflow
CriticalJournal approval, disbursementDeterministic only — no AI execution
Models & data: Cloud frontier (Claude/GPT-4) default; enterprise API contractually prohibits training on your data. Local LLM only when regulatory/client requirements explicitly prohibit cloud for that data flow.
Cost: API-only $500–2K/mo. Postgres audit log + dashboard. No hardware, no vendor onboarding needed in diagnostic.
IP & evidence: Every write requires validated evidence (Velarion pattern). Custom code/prompts licensed to you perpetual, royalty-free; generalized components reusable by me.

For counsel / auditors

If you need the full controls memo (SOW guardrails, SOC-adjacent logging schema, segregation matrix, and change management flow), I provide it in diligence — it's part of the engagement package. The five layers above are the summary your audit committee will want on one page.

How to engage →See the process →