Governance That Decides, Not Just Detects
Every AI SOC, GRC, and posture tool tells you something looks wrong after the fact. Fintra decides - in real time, per action - whether a payment, filing, data access, or agent tool-call should proceed, and records why.
Illustrative product view
The gap every other tool leaves open
AI security, SOC, and GRC platforms are built to observe: they scan posture, flag anomalies, and collect evidence for auditors. None of them stand in the path of a specific business action and decide, in the moment, whether it should happen. That decision - allow this payment, step up on this data access, deny this agent tool-call - is where risk actually becomes loss. Fintra fills exactly that gap with a Policy Decision Point.
What a decision looks like
| Action | Verdict | Why |
|---|---|---|
| Read a customer record in-tenant | allow | Read sensitivity, scope contained |
| Write or update a sensitive field | require_step_up | Write to sensitive data |
| Payment to a brand-new payee | require_step_up | Blast radius + new counterparty |
| Access another tenant’s data | deny_recommended | Tenant isolation, risk 95 |
| Malformed or ambiguous request | human_review_required | Fail-soft, never a silent pass |
How the decision is made
From request to recorded verdict
- 1
Enforcement point calls the PDP
A policy enforcement point - the Fintra MCP guard, a payment hook, an app - calls POST /api/v1/aegis/pdp/decide with the action envelope.
- 2
Deterministic rules run
Tenant isolation, scope containment, then a sensitivity ladder (read / write / sensitive) evaluate the request in a stateless fast path.
- 3
A verdict and score return
One of seven verdicts plus a risk score, an Action Trust Score, a trust band, and an enforcement view come back - same input, same answer.
- 4
The verdict is recorded
A reproducible ledger hash is written to the hash-chained Trust Ledger so the decision is provable later.
- 5
Evidence is emitted when enabled
When a compliance sink is configured, the governed action maps to controls and produces evidence automatically.
Who it’s for
- Teams deploying AI agents that can touch money, records, or customer data
- Security and compliance leads who have monitoring but no real-time control point
- Finance orgs that need per-action authorization on payments and filings
- Platform teams standardizing how humans, service accounts, and agents are governed
Frequently asked questions
What is AI action governance?
AI action governance is deciding, in real time and per action, whether a specific business action should proceed - a payment, a filing, a data access, or an AI agent tool-call. Unlike monitoring or posture tools that observe after the fact, it returns a verdict before the action executes and records why.
How is this different from an AI SOC or GRC tool?
AI SOC and GRC tools detect issues, monitor posture, and collect evidence - they observe. Fintra adds the decision layer they lack: a policy decision point that returns an authoritative verdict for each action and writes it to a tamper-evident ledger. Detection tells you what happened; action governance changes what happens.
Does Fintra actually block actions itself?
Fintra returns the verdict; your enforcement point acts on it. Aegis runs in simulation mode by default, so containment and revocation are simulated rather than executed. It is best described as a decision and authorization fabric that your systems consult before they act.
What kinds of actors can it govern?
The decision point covers humans, service accounts, OAuth apps, CI bots, AI agents, and MCP tools on one model. Whatever the actor, the same tenant-isolation, scope-containment, and sensitivity rules apply, so agents are held to the same standard as people.
Stay in the loop
One practical finance briefing a week - new guides, checklists, and benchmarks.
Put a decision point in front of every action
See how Fintra returns a verdict per action and records it to a tamper-evident ledger.
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