FINANCE

Nightly expense outlier scan with statistical anomaly detection

Runs every night over the day's Airtable expense rows, flags spend that is a statistical outlier versus each employee's historical pattern.

CategoryFinance
Enginesim
Difficultyadvanced
Triggerschedule
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNightly schedule fires
  • ActionPull day's expense rows + employee history from AirtableAirtableAirtable
  • LogicScore deviation from baseline, filter out normal spend
  • LogicRank remaining outliers by severity
  • OutputEmail ranked outlier digest to financeGmailGmail

What it does

This workflow scans the expenses logged in Airtable during the day and finds the ones that don't fit. Instead of a fixed dollar threshold, it compares each charge to the employee's own spending history for that category and surfaces anything that is a meaningful deviation, like a 4x-normal dinner or a first-ever charge in a new category. It then emails finance a single ranked digest so they wake up to a prioritized list rather than a raw export.

When to use it

Use it when expenses live in Airtable and flat thresholds miss too much, either flagging routine spend for high earners or ignoring suspicious small charges. Good for a finance team that wants one daily review queue instead of real-time noise.

How it works

  1. 1A nightly schedule triggers the run.
  2. 2The day's new expense rows are pulled from Airtable along with each person's trailing history.
  3. 3Each charge is scored for deviation from the employee's category baseline; normal items are filtered out.
  4. 4Outliers are ranked by severity and annotated with the reason they were flagged.
  5. 5A formatted digest email is sent to finance with the ranked list and direct row links.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect AirtableBases, tables, views, automations.
  2. 2
    Connect GmailRead, draft, send, label.
  3. 3
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  4. 4
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  5. 5
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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