Finance AI Governance

Finance AI Governance Before Regulated Action

AI governance for finance, banking, capital markets, compliance, MRM, and regulated AI outputs before they become business consequence.

Finance commitment boundary

Govern the moment financial language becomes an organizational act

OntoGuard evaluates proposed financial-services output before it is released to a customer, advisor, reviewer, record, or downstream workflow. It supports decision authorization and evidence routing; it does not independently make regulated financial decisions.

EvidenceIs the statement supported and conflict-free?
AuthorityIs the proposed movement within delegated authority?
ConsequenceDoes customer or market impact require review?
ReleaseMay this output bind the enterprise now?
Priority workflows

Finance use cases that benefit from pre-action authorization

Customer-facing guidance

Financial guidance, advisor-assist output, suitability-related language, and customer communications.

Decision support

Credit or underwriting support, KYC or onboarding review, and exception-routing support.

Controlled release

Compliance-review summaries and market commentary before external distribution.

Common admissibility failures

Why plausible language may still be inadmissible

  • Unsupported financial statement
  • Missing or conflicting evidence
  • Delegated authority not established
  • Unverified suitability context
  • Policy applicability uncertainty
  • Reviewer assignment missing
  • Citation-linkage gap
  • Attempted release before required review
Sanitized decision example

A customer-facing financial guidance release

Proposed movement
Release AI-generated customer-facing financial guidance.
Decision
◆ ESCALATE
Release authorized
■ No — withheld
Reason
Delegated authority is not established and supporting evidence is incomplete.
Route
Human review
Protected effect
Not formed in the controlled proof environment.
Evidence and authority posture

What OntoGuard decides and records

Evidence state

Available, missing, conflicting, and decision-relevant evidence are made explicit.

Authority state

Delegated authority, applicable constraints, and reviewer authority remain distinct fields.

Human-review route

Escalation records who must review, why review is required, and whether closure is pending.

Proof produced

Decision state, release status, reason codes, route state, no-bind posture, and selected PDF/JSON evidence.

Starting point and pilot boundary

Start with representative outputs, then prove the route

AI Output Risk Scan

Begin with 10–25 prompts, outputs, logs, intended action labels, and workflow labels. The scan maps risk, uncertainty, review burden, and selected proof-packet candidates.

Production route evidence

Controlled event-level no-bind proof is available today. Production L5 route completeness requires customer-specific route integration, endpoint enforcement, fail-closed evidence, replay records, and outcome closure.

OntoGuard maps decision-relevant evidence, constraints, and regulatory context. It does not provide legal certification or replace authorized financial, legal, compliance, or operational decision-makers.

Evidence state, buyer roles, and reviewer authority

Evidence available

Source records support part of the proposed guidance, but applicability, recency, or customer context may still be incomplete.

Evidence missing or conflicting

Missing suitability context, unresolved source conflict, or absent supporting documentation prevents release authorization.

Buyer roles

AI product, model risk, compliance, legal, operations, and business owners can inspect the same decision and proof posture.

Reviewer authority

Escalation is not closed until the reviewer is assigned, qualified, delegated to decide, and the outcome is recorded.

Decision-to-proof sequence

The proposed finance output is classified as a movement, candidate evidence is retrieved, evidence and authority are evaluated, ALLOW/BLOCK/ESCALATE is returned, unauthorized release is withheld, and the packet records the decision, route, release state, and no-bind posture.

First Risk Scan requires

10–25 representative prompts and outputs, intended action and audience labels, workflow context, available evidence references, and examples of current human review.

What is not claimed

No autonomous regulated financial decision, legal or compliance certification, guaranteed suitability, universal production enforcement, or measured hard-dollar ROI without buyer data.

Richer evidence-state example

A proposed customer communication cites a general product description and recent market data, but the packet lacks customer-specific suitability context and proof that the authoring workflow has delegated release authority. BM25 retrieval can surface the exact product language and policy terms; semantic governance can connect them to the proposed communication. The resulting evidence is useful but incomplete. OntoGuard returns ESCALATE, withholds release, identifies the missing context, and routes the case to the qualified financial or compliance reviewer defined by the institution.

Closure requires a recorded reviewer identity, applicable authority, reviewed evidence, final disposition, and the exact version approved or refused. Only then can the proof record distinguish an approved revised communication from a proposal that remains withheld.