CUSTOMER SUPPORT

Refund Fraud: Pre-Approval Gate via Refund Webhook

Receives a refund-approval webhook from your support tool, runs a synchronous Postgres linked-account and lifetime-refund check.

CategoryCustomer Support
Enginesim
Difficultyintermediate
Triggerwebhook
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerRefund-approval webhook receivedHTTP webhook
  • ActionQuery Postgres for links, limits, active holdsPostgreSQLPostgres
  • LogicApply policy: deny on hold/over-limit, else allow
  • ActionWrite decision and reason to audit logPostgreSQLPostgres
  • OutputReturn allow/deny response; Slack on denySlack

What it does

Acts as a real-time decision endpoint your support or commerce app calls the instant an agent clicks Approve Refund. It synchronously evaluates the requester against linked accounts and lifetime refund limits and returns allow or deny, so risky refunds are stopped at the button rather than reversed after the fact.

When to use it

Use this when you can wire a webhook into your refund flow and want the fraud check to happen inline, not asynchronously. Ideal for high-value refunds where issuing first and clawing back later is costly.

How it works

  1. 1An HTTP webhook fires from your support tool carrying the order and customer identifiers.
  2. 2Postgres is queried for linked accounts, lifetime refund total, and any active fraud holds.
  3. 3A logic step applies the policy: deny on active hold or over-limit, allow otherwise.
  4. 4The decision and reason are written to the Postgres audit log.
  5. 5The flow returns a structured allow/deny response to the caller; denials also post to Slack for visibility.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect HTTP webhookTrigger any URL on agent actions.
  2. 2
    Connect PostgresAny Postgres URL — query, write, migrate.
  3. 3
    Connect SlackChannels, DMs, threads, mentions.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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