FINANCE

Pre-Close Rev-Rec Exception Finder for Unmapped Stripe Charges

Each night during close week, pulls new Stripe charges, checks each one against the recognition-schedule table in Snowflake.

CategoryFinance
Enginesim
Difficultyintermediate
Triggerschedule
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNightly schedule during close week
  • ActionPull recent Stripe chargesStripeStripe
  • ActionQuery rev-rec schedule table in SnowflakeSnowflakeSnowflake
  • LogicKeep charges with no matching schedule; classify reason
  • OutputPost exception list to close Slack channelSlack

What it does

Scans recent Stripe charges and surfaces the ones that don't tie to a revenue-recognition schedule, so they get resolved before month-end close instead of becoming an audit finding.

When to use it

Run it nightly during close week (or the last five business days of the month) when your team needs to be confident every dollar of cash collected has a place to be recognized. Ideal for SaaS and subscription businesses where deferred revenue lives in Snowflake and ad-hoc or one-off charges slip through.

How it works

  1. 1A nightly schedule fires during the close window.
  2. 2The flow pulls Stripe charges created since the last run, including metadata, product, and invoice references.
  3. 3It queries the `rev_rec_schedule` table in Snowflake and left-joins each charge by charge ID and invoice ID.
  4. 4A filter keeps only charges with no matching schedule row, then classifies each as one-time, missing-product-mapping, or refunded.
  5. 5The exception list (amount, customer, reason) is posted to the close Slack channel with a running total of unmapped dollars.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect StripeCustomers, subscriptions, payments.
  2. 2
    Connect SnowflakeWarehouses, queries, shares.
  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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