AI Agent Authority for Financial Services
At the moment of action, authority must be proved — not assumed.
Agent Trust Gate™ demonstrates a pre-action trust boundary for consequential AI-agent actions where exact scope, amount, account, jurisdiction, evidence and accountable human authority may matter before execution or settlement.
The control question
Model governance can address how an AI system was built and supervised. ATG focuses on a narrower execution question: may this exact agent perform this exact consequential action now, under this exact authority and evidence?
An agent may be capable of initiating a transfer, changing a beneficiary, approving remediation or triggering a high-impact operational workflow without being authorised for the exact amount, account, customer context, jurisdiction or risk tier involved. The ATG control model is designed to make that authority check explicit before consequence.
Illustrative action categories
- payments, transfers and settlement-adjacent instructions;
- lending or credit actions requiring delegated authority;
- fraud, AML or compliance escalations;
- customer remediation such as refunds, repayments, credit notes or write-offs;
- market, treasury or other high-impact operational actions subject to policy limits.
Human authority when required
A stored approval flag is not treated as enough. The demonstrator can model whether the approving natural person is active, authenticated through organisation-controlled evidence, authorised for the exact action type and amount, independent from the requester where policy requires it, and supported by any second approval required by policy.
The public model is deliberately crypto-agile: it can represent strong organisation-controlled human authentication today while keeping algorithm identifiers, key references and verification policy replaceable. It does not claim that present-day passkeys or signatures are automatically post-quantum safe.
Exact-action binding and replay control
A GatePass is intended to bind authority evidence to one canonical action rather than to a broad instruction such as “approved payment.” If the amount, destination, account, action type or other protected field changes, the action can be treated as a different action and refused. Expiry and one-use nonce concepts reduce the risk that an old authorisation is replayed against a later request.
Reviewable evidence
Decision evidence and simulated execution evidence are kept distinct so a reviewer can inspect what was proposed, why it was allowed or refused, and whether the later action still matched the authorised action. The goal is a human-understandable trust receipt backed by the underlying technical proof rather than a vague statement that “the AI was approved.”
What ATG is not
ATG does not replace financial regulation, model-risk management, transaction monitoring, banking infrastructure, payment rails, compliance judgement or enterprise identity systems. It is not FCA-authorised or otherwise represented as regulator-approved. The public implementation is a local synthetic demonstrator and does not move real money, access customer data or execute live financial actions.
Read the exact-action authority control model → Review the evidence path → Open the Human Authority demo →
Agent Trust Gate™ — Exact-Action Authority for AI Agents. Local demonstrator only.