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Retail AI agent · Payment fraud

Payment-Fraud & Chargeback-Recovery AI Agent

Score the transaction, hold the risky ones for a short review rather than declining outright, and leave every decline above the threshold to the fraud analyst who decides it.

Typical delivery
4–6 weeks
Deployment
Your stack
Analyst decides
Hold, not block
After launch
Agent Care

What this agent does

Scores the order, not the person behind it

In

  1. 01

    Ingest orders, authentication results and payment signals from supported commerce, gateway and risk sources.

  2. 02

    Normalise the fields, and carry every signal forward with the source it came from.

Reason

  1. 03

    Score the transaction and rank it against the review queue.

  2. 04

    Apply the rules, thresholds and review policy configured for the merchant.

  3. 05

    Keep the score about the transaction, and exclude protected characteristics and their close proxies.

Decide

  1. 06

    Word any customer message about the order alone, not as a claim about the customer.

  2. 07

    Route every decline above the threshold to the fraud analyst who decides it.

Out

  1. 08

    Retain the score, its top features, the model version, the rules fired and the reviewer.

  2. 09

    Execute write actions only inside the approval boundaries agreed during implementation.

Product statement

The agent scores; the fraud analyst decides — and a wrongly declined order is a customer who simply leaves, while a wrongly filed representment is a network-rule matter with its own limits.

Example workflow

One order, score to decision

  1. 1Order receivedA checkout, a stored-credential reorder or a card-not-present transaction
  2. 2Features assembledAuthentication result, payment signals, order history and tenure, each with its source
  3. 3Transaction scoredThe score, its top contributing features, the rules fired and confidence
  4. 4Risk checks appliedExcluded-feature checks, threshold policy, message-wording rules and confidence threshold

No human action required

Stages one to four run unaided — the agent scores and ranks, and the analyst's lane opens at the confidence gate for every decline that has to be reviewed.

5DecisionSplits at the decision threshold
Low risk

Goes to the fraud analyst to decide.

Elevated risk

Adds a senior risk read first.

Fraud-analyst review

The order is held with its score, its top features and the confidence.

Release · Uphold · Escalate to risk

Decided — released or declined

  1. 6Order systems updatedOnly where write access and approval policy allow it
  2. 7Decision evaluatedFalse-decline rate, network programme ratios, representment outcomes and customer appeals

Overturns

Every analyst release is counted in the evaluation.

What should not run autonomously

Human approval stays in control

Outside the boundary — human approval required

8 items

  • Declining any order above the review threshold.
    • Adding any customer to a permanent block list.
    • Setting a score threshold or a fraud rule.
    • Approving a representment packet before submission.

  • Automation boundary

    Agent acts unaided

    • ✓Score transactions and rank them for the analyst review queue.
    • ✓Place a short, time-boxed hold pending that review.
    • ✓Assemble and verify representment evidence.
    • ✓Monitor network programme ratios and escalate as they approach.

    Any write happens inside the boundaries agreed at implementation, never ahead of approval.

    • Wording of a customer-facing decline or dispute message.
    • Deploying a model version and signing its disparity test.
    • Onboarding a data source and classifying it for consumer-report status.
  • Remediation and notice posture after a wrongful decline.

Example output

One decision, annotated

Everything the agent proposes is attached to the signals it was drawn from.

Fraud output · single order

Illustrative example
Customer
Repeat domestic customer
Agent action
Held for analyst review rather than declined outright
Order value
$412.00
Top contributing feature
New shipping address
Confidence
88%
Customer wording
Transaction-neutral only

As received

Taken from the order, the authentication record and this customer's own history with the merchant.

Signals used

  • Authentication result
  • Order and tenure history
  • Device and address match

Why this hold

The score is about the transaction, not the customer and a person still decides.

What the score decides

Beyond the configured threshold the hold goes to the fraud analyst rather than standing.

Action

ReleaseUpholdEscalate to risk

Value

Where AI adds value

The same four claims, placed at the point in the workflow where each one applies.

Where the value lands

Value 01 – 04

Every transaction

From the checkout and the gateway

03Scoring

Score the transaction

Draw on authentication results, payment signals and the customer's own history with the merchant.

01Approved path

Decline less, review better

Routine low-risk orders clear without an analyst touching them.

02Human review

Send review to the costly calls

High-value, low-tenure and cohort-flagged orders are marked, so the analyst's read starts where a wrong call costs most.

04

Build an evidence trail

The score, its inputs and the analyst who reviewed it stay with the decision.

Integrations

Typical integrations

Five system groups connect to the same agent. Which of them are in scope is decided in discovery.

  • Gateway-native fraud scoring

    • Stripe Radar
    • Adyen RevenueProtect
    • Sift
    • ClearSale

  • Fraud decisioning platforms

    • Signifyd
    • Riskified
    • Forter
    • Kount

  • Dispute and representment

    • Chargebacks911
    • Justt
    • Midigator
    • Chargeflow

Agent

Payment fraud & chargeback recovery

  • Reads the order
  • Scores the transaction
  • Holds for review

  • Pre-dispute and workflow

    • Verifi
    • Ethoca
    • Acquirer and gateway APIs

  • Observability & evaluation

    • OpenTelemetry
    • Langfuse
    • Supported monitoring/evaluation sources

Integration availability depends on the client's existing systems and API access.

Agent controls

Six layers between the model and the decline

The stack nests inward; the map below names what each layer misses.

L6 · Outermost — last line of defence

Inward → L1 · closest to the model

L6Rollback / safe modePull scoring back to ranking-only when evaluation or production signals degrade.Roll back
L5Version monitoringTrack model, prompt, threshold and rule-set changes.Track
L4TraceabilityRecord the score, its top features, the model version, the rules fired and the reviewer.Record
L3Fraud-analyst reviewHold declines for the named analyst; it governs the decision, not whether the score was right.Gate
L2Policy guardrailsTest decisions against excluded features, threshold policy and message wording; a failure returns the case.Restrict
L1Confidence thresholdsRoute low-confidence scores to a senior risk read before the analyst decides.Require review
Model coreOrder scored — the score, its top features, the rules fired and confidence
L1 – L2
Test whether a decision may stand
L3
Puts the decline in an analyst's hands
L4 – L5
Keep the score and its inputs reconstructable
L6
Widens review rather than declining more

How Nestack evaluates it

Evaluate the decision workflow — not only the fraud that was caught.

Coverage runs the whole depth of the workflow, and every layer is cut by slice.

Surface — the outcome the customer meets

  1. E1Final-output evaluationWas the decline supported by transaction evidence rather than by who the customer is?
  2. E2Step-level evaluationDid the agent use the right signals, thresholds and review policy?
  3. E3Tool evaluationDid it write the correct order and the correct hold state?
  4. E4Confidence calibrationDo low-confidence scores actually attract more analyst releases?
  5. E5Slice evaluationHow does performance change across specific customer segments?
  6. E6Business outcomeHow many legitimate orders were declined, held to abandonment or wrongly represented?

Floor — the transaction that stands or falls

Failure modes

Where each failure originates in the agent

Seven modes across the decision lifecycle.

Agent lifecycle

Direction of processing →

  1. 01 · Retrieval

    1 mode

    • FD-03

      Stale reputation record

      A recycled address carries a prior ring's history onto a new customer.

    Stage gathers

    Orders, authentication results, with the source each came from

  2. 02 · Reasoning

    2 modes

    • FD-04

      Gift order read as fraud

      A billing and shipping mismatch on a gift is scored as risk.

    • FD-06

      Eligibility miscounted

      Transactions outside the qualifying window are counted as evidence.

    Stage proposes

    The score, its top features and confidence

  3. 03 · Tool / write

    2 modes

    • FD-02

      Permanent block written

      A time-boxed hold is written as a standing block across systems.

    • FD-05

      Wrong evidence attached

      A representment carries a delivery record from another order.

    Stage writes

    Only where write access and approval policy allow it

  4. 04 · Output

    1 mode

    • FD-01

      Accusation in the message

      A decline notice tells the customer their order was fraudulent.

    Stage returns

    The message and the decision the customer meets

  5. 05 · Change / Version

    1 mode

    • FD-07

      Silent calibration shift

      A model refresh moves the score scale under a fixed threshold.

    Stage tracks

    Model, prompt, thresholds and rule sets

  • Sev-1 · a decision made outside the boundary
  • Sev-2 · a legitimate order is declined
  • Sev-3 · a signal degrades
See the complete Retail failure-mode catalogue

Affected slices

Overall approval rates can hide one segment

The false-decline rate is the share of legitimate orders declined, or held until the customer abandons them. Nestack reports it by slice as a lift on the all-transaction baseline.

Slice performance — reported separately, not only in aggregate

Illustrative example
SliceFailure rateLiftLift vs. thresholdStatus
First-time, forwarder, high value6.5%3.8×Review
Consumer-report identity checks4.8%2.8×Review
Established customers, real victims2.4%1.4×Watch
Repeat domestic, stored credential1.2%0.7×Normal

Bar: false-decline lift vs. the all-transaction baseline · scale 0–4.0× · tick marks the 2.0× review threshold

2 of 4 slices over threshold

Evidence-linked improvement

A cycle closes on a case, not a review

A cycle finishes when the failure has a case, an owner and a release that must pass it.

Improvement cycle · five stages

Switchback — the path turns at Improve and returns at Learn

  1. 01

    Detect

    False declines rise in one customer segment.

  2. 02

    Diagnose

    While the gap in that segment stays open, the analyst replays the declines and their features until one cause is left.

  3. 03

    Improve

    The correction is stamped and linked to the decisions that produced it.

  4. 04

    Verify

    Re-running the affected cases is the release condition.

  5. 05

    Learn

    A permanent case, plus a change to the decision policy.

  6. Learn → Detect

    The return edge. Each detection meets more standing cases than the one before.

Typical build scope

Twelve workstreams across six weeks

The build scope read against the delivery timeline. Week structure follows the six-week plan — discovery, sources, decision workflow, evaluation, integration, then production validation and handover.

Workstream

Week 1Week 2Week 3Week 4Week 5Week 6

  1. 01Decision workflow discovery and boundary definition.Week 1
  2. 02Gateway and processor-source assessment.Week 1, Week 2
  3. 03Rule, threshold and review-policy mapping and rule mapping.Week 1, Week 2
  4. 04Order and payment-record ingestion.Week 2
  5. 05Scoring logic and signal-provenance.Week 2, Week 3
  6. 06Confidence scoring and review routing.Week 3
  7. 07Fraud-analyst review.Week 3, Week 4
  8. 08Gateway, risk and dispute integration.Week 5
  9. 09Decision regression cases.Week 4, Week 5
  10. 10Guardrails and decline controls.Week 4
  11. 11Score-trail instrumentation.Week 5, Week 6
  12. 12Deployment, documentation and Agent Care handover.Week 6

12 workstreams · 6 weeks · bar shows the weeks a workstream is active — several run in parallel

Final scope and sequence confirmed in discovery

Engagement tiers

What each tier includes

Rows are the capabilities named in each tier's scope. Higher tiers include everything below them.

Capability✓ in scope · — not at this tierPilotOne channel, one payment setProductionProduction decision volumeAdvancedMultiple channels / regions
Introduced at Pilot
Scoring to your rules and thresholds✓✓✓
Fraud-analyst review✓✓✓
Decision-quality baseline✓✓✓
Introduced at Production
Reporting by segment—✓✓
Review workflow in your systems—✓✓
Approved write-back to order systems—✓✓
Risk-platform integration—✓✓
Introduced at Advanced
Multi-region decision rule sets——✓
Multi-stage risk approvals——✓
High transaction volume——✓
Enterprise risk controls——✓
Build priceFrom $5,000From $8,000Custom quote
Final build price
Confirmed after discovery based on integrations, workflow complexity, transaction volume, approval controls and deployment requirements.
Separate from build
Build pricing is separate from recurring Agent Care, which covers managed monitoring, evaluations, incidents and verified improvements after launch.

What we need from you

What you bring, and what we build with it

Each input maps to a piece of build scope and a week in the delivery timeline.

  1. 01Your decline rules, thresholds and review policy

    Rule, threshold and review-policy mapping

    Week 1

  2. 02Representative past decisions

    Scoring baseline, feature review and provenance binding

    Week 2

  3. 03Your vendors and their consumer-report status

    Threshold and review-policy mapping, and the automation boundary

    Week 1

  4. 04Access to relevant APIs, feeds or exports

    Gateway, risk and dispute assessment, then integration setup

    Week 2

  5. 05Declines you had to apologise for

    Decision cases and failure-mode testing

    Week 4

  6. 06Which declines must be reviewed before they stand

    Risk bands, review routing and decline controls

    Week 3

  7. 07A named analyst to review declines

    Analyst review workflow, then pilot and production validation

    Weeks 5–6

Nothing else is required

Deployment, documentation and Agent Care handover are ours.

Delivery timeline

Four phases across six weeks

Bands follow the work rather than the calendar, and evaluation shares week 5 with the pilot.

Phase

W1

W2

W3

W4

W5

W6

  1. DiscoveryW1
  2. BuildW2 – W3
  3. EvaluateW4 – W5
  4. Pilot & LaunchW5 – W6

Week focus

W1Decision workflow discovery, threshold mapping and the automation boundary

W2Signal and network data connected

W3Scoring workflow, confidence logic and review controls

W4Decision cases and decline guardrails

W5Dispute integration, pilot decisions and targeted corrections

W6A live decision window reviewed by the analyst, then handover

Reading the band
No padding — week 5 genuinely carries both evaluation and pilot.
At the end of W6
Checks close on live decisions and Agent Care takes the monitoring.
Duration
Six-week plan shown · typical delivery 4–6 weeks depending on scope confirmed in discovery.

Next step · Retail AI agent

Build a fraud agent that is precise about which law actually applies.

A merchant declining a card is not a creditor taking adverse action; the real hooks are state unfair-practices and public-accommodation law, and fair-credit-reporting duties where a consumer report is used. Show us your decline rules and who signs a representment.

Typical delivery
4–6 weeks
Deployment
Your risk stack
Analyst decides
Hold, not block
After launch
Agent Care available

Nestack Agents · Payment fraud and chargeback recovery

AGT-RT-13 · Agent Care available after launch

Build a fraud agent

Four questions so the call starts from your actual setup — then pick a time that suits you.

About you
Your orders

No obligation. We’ll map the workflow, name the automation boundary and tell you if an agent is the wrong answer.