FINANCE

Daily corporate-card spend policy audit

Each morning pulls the prior day's settled Stripe Issuing transactions, flags any that violate your spend policy.

CategoryFinance
Enginesim
Difficultybeginner
Triggerschedule
Steps5
Setup~5 min

How it runs

The automated pipeline, trigger to output.

  • TriggerDaily morning schedule
  • ActionFetch yesterday's settled Stripe transactionsStripeStripe
  • LogicFlag transactions that violate spend policy rules
  • ActionWrite each violation as a Notion database rowNotionNotion
  • OutputPost daily summary and violation count to SlackSlack

What it does

Once a day it reviews every corporate-card transaction that settled yesterday and surfaces the ones that break policy: over a per-transaction limit, in a restricted category, or from a blocked merchant. Compliant spend is summarized; violations are itemized with the cardholder, amount, merchant, and the specific rule broken. The result lands in a Notion database that finance reviews like a queue.

When to use it

Use this when point-of-sale blocking is too blunt and you prefer a daily human review of edge cases. Good for teams that allow most spend but want a standing record of exceptions and a paper trail for month-end close.

How it works

  1. 1A scheduled trigger fires every morning.
  2. 2The flow queries Stripe for all transactions that settled in the previous 24 hours.
  3. 3A logic step evaluates each transaction against the policy rules: amount caps, restricted MCCs, and merchant denylist.
  4. 4Clean transactions are tallied into a daily summary.
  5. 5Each violation is written as a new row in the Notion exceptions database with rule, amount, and cardholder.
  6. 6The summary plus violation count is posted to Slack so reviewers know the queue is ready.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect StripeCustomers, subscriptions, payments.
  2. 2
    Connect NotionPages, databases, comments.
  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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