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Illustrative scenario

Not based on a specific customer deployment. The company, figures, decisions, and outcomes below are a constructed example that shows how Intended’s mechanism applies to this kind of problem. They are not measured results from a named customer. Where we publish a real, attributed customer outcome, we will say so explicitly.

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Financial Services

Governing AI-Initiated Fraud Actions at a Digital Bank

Consider a digital-first bank whose AI agents handle transaction monitoring, account actions (freezes, limit changes), KYC verification, and customer service automation across a high volume of daily transactions.

01 · the challenge

The kind of problem this addresses.

$$$
fraudulent transactions AI agents could execute before a human ever sees them
Freezes
AI-initiated account locks that hit legitimate customers with no graduated response
No trail
regulatory-grade audit evidence for AI-driven account actions

02 · how it works

See the difference.

AI detects suspicious pattern

3 rapid transfers to new payee, total $47,000

AI freezes account

No graduated response, no risk scoring

Legitimate customer locked out

Wire transfers for home purchase

Customer complaint filed

No audit trail to explain AI decision

03 · the solution

What they deployed.

  • Installed Banking Operations domain pack with fraud detection, KYC, and account action intents
  • Configured graduated response: step-up auth for MEDIUM risk, freeze for HIGH/CRITICAL only
  • Customer behavioral context integrated into risk scoring (historical patterns reduce score)
  • All account actions require authority tokens with regulatory-grade evidence chains
  • Connected core banking system, fraud detection platform, and customer notification service

04 · implementation

From zero to governed.

Week 1

Map

Catalogued all AI agent account actions. Identified 18 action types across fraud, KYC, and customer service.

Week 2

Configure

Installed Banking Ops pack. Configured graduated response policies, behavioral context scoring, and escalation chains.

Week 3

Integrate

Connected core banking API, fraud detection engine, and customer notification services via Intended connectors.

Week 4

Enforce

Enabled enforcement. First graduated response (step-up auth instead of freeze) within 2 hours of going live.

05 · illustrative outcomes

What this is designed to deliver.

Modeled figures for this scenario — what the workflow above is built to achieve, not measured results from a named customer.

0%

Account actions token-gated

Every freeze, limit change, and block carries authority

0%

Actions with audit trail

Regulatory-grade evidence by design

0

Graduated response tiers

Step-up auth before any hard freeze

<0ms

Per-decision overhead

Design target, in-line with the transaction

06 · decision replay

Example decisions, full trace.

Sample decision records that show the shape of the evidence Intended produces. Illustrative, not drawn from a live customer’s logs.

2026-03-15 03:14:22banking.fraud.transaction-reviewRISK: 68/100ESCALATE24ms

AI flags 3 rapid transfers totaling $47K to new payee -- customer has home purchase history

Resolved by: Graduated response: step-up authentication (customer verified in 42s)

2026-03-15 04:33:11banking.fraud.account-freezeRISK: 96/100ALLOW12ms

AI detects credential stuffing attack on account, 47 failed login attempts from 12 IPs

Resolved by: Policy: auto-freeze for credential stuffing pattern (CRITICAL risk)

2026-03-15 08:45:07banking.kyc.identity-reverificationRISK: 52/100ALLOW28ms

AI triggers KYC re-verification for customer with address change + large withdrawal

Resolved by: Policy: KYC re-verification auto-approved for qualifying triggers

2026-03-15 12:18:44banking.fraud.transaction-blockRISK: 100/100ALLOW8ms

AI blocks $180K wire to sanctioned entity -- OFAC match on beneficiary

Resolved by: Policy: auto-block for OFAC sanctions match

2026-03-15 15:22:08banking.customer.limit-changeRISK: 44/100ESCALATE22ms

AI increases daily transfer limit from $10K to $50K based on customer request

Resolved by: Relationship Manager (approved after customer call in 6m)

the takeaway

Fraud controls usually trade off against customer experience: catch more, and you freeze more legitimate accounts. Intent classification plus graduated response breaks that trade-off — step-up auth instead of a freeze, verification instead of a lockout — and every action leaves a regulatory-grade evidence trail.

Why this pattern matters — not a customer quote.

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Intended — Intent Verification Infrastructure for Autonomous Agents