Model-change approval
Show why a change cleared governance, what evidence supported it, what stayed uncertain, and where review occurred.
Financial services
Model decisions that can survive examiner review.
Banks, funds, fintechs, and market infrastructure teams are already using models and AI agents inside decisions that examiners, boards, customers, and counterparties may challenge later. Forge's proof layer records the supplied evidence, encoded policy result, uncertainty, and human boundary.
Model governance
Trading controls
Credit exceptions
AI workflow review
In plainer terms: start by paper-testing one proposed refund, payment, credit, or trading decision. A real pre-action check requires scoped access and a qualified, customer-deployed, validated, exclusive protected boundary the agent cannot bypass.
Where it hurts
The decision is high stakes, but the proof is scattered.
- Model changes. Why the new model version, feature set, threshold, or override cleared governance.
- Trading and exposure controls. Why an AI-assisted or automated workflow allowed, held, or escalated an action.
- Credit and risk exceptions. Why an exception was approved, denied, or sent to a human decision owner.
- Regulatory review. How the firm shows the evidence, policy, uncertainty, and sign-off without asking the examiner to trust internal logs.
What Forge adds to a financial workflow.
| Messy evidence | Model output, validation notes, control checks, counterparty evidence, approvals, policy text, exceptions, and missing facts. |
|---|---|
| Allowed actions | Proceed, hold, escalate, reject, approve with conditions, or any equivalent action menu the firm defines. |
| Proof trail | The controlling evidence, rule applied, confidence, uncertainty, alternatives, and human-review boundary. |
| Calibration | Only authorized firm outcomes with explicit retention opt-in create tenant-local calibration state. Without retention opt-in, no calibration row is written. |
First workflow candidates.
AI agent action gate
Evaluate selected actions before execution only through a qualified, customer-deployed, validated, exclusive protected boundary the agent cannot bypass. The public walkthrough does not authorize, block, or execute a financial action.
Exception review
Turn one recurring exception workflow into proof a CCO, risk owner, or examiner can inspect.
Regulatory anchors.
Forge supports the documentation and evidence obligations behind modern model governance. It does not certify compliance, and no Forge proof trail is a legal conclusion. That line stays with your counsel and your regulators.
| SEC Marketing Rule | Preserve the recorded basis for a performance or capability claim, then verify the issued complete record under an independently pinned signer and replay the governed result separately. |
|---|---|
| Model-risk governance, SR 26-2 (successor to SR 11-7) | This is your firm's own supervisory regime for covered traditional modeling uses, not something Forge provides. SR 26-2 expressly excludes generative and agentic AI. For an applicable non-agentic model workflow, a qualified integration can bind a specific output to the recorded model version, inputs, and policy. The public walkthrough is not production evidence. |
| NIST AI Risk Management Framework | The proof trail can support Govern, Map, Measure, and Manage documentation. Calibration uses only authorized outcomes the firm explicitly opts in to retain; framework applicability remains the firm's assessment. |
| EU AI Act, Article 10 | Data and data governance. Forge binds every normalized evidence item into the complete proof trail and can carry a caller-supplied source content hash. The complete-record signature is the integrity check. Source freshness or verification affects a decision only when the integration supplies and evaluates that status as evidence or an explicit constraint; Forge does not infer it from a raw file. |
Illustrative proof trail: a model-driven suitability decision.
Consider an automated workflow that proposes a model portfolio while a customer reports a short liquidity horizon and one required input remains stale. The important result is not a model score by itself. It is a defensible reason the proposal requires review before it reaches the customer.
What was known
The proposed allocation, stated liquidity need, customer risk information, and freshness of required inputs.
Why review was required
The proposal conflicted with the stated liquidity horizon and one required basis remained unresolved.
Who decides next
The customer's licensed and authorized reviewer determines the next action. Forge does not recommend or execute a trade.
Start with the call your examiner would ask about first.
Forge is live, tested, and ready for a scoped enterprise integration. It can scope one financial workflow with synthetic, sanitized, or approved sample evidence. Production use remains conditional on security, audit, build, deployment, and operational qualification.