FINANCE

Large-Variance Controller Escalation

After the morning reconciliation completes, checks the day's total unexplained variance against a threshold and, when breached, opens an Asana task for the controller and pages…

CategoryFinance
Enginesim
Difficultyintermediate
Triggerschedule
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerPost-reconciliation schedule
  • ActionRead day's unexplained variance from PostgresPostgreSQLPostgres
  • LogicEvaluate against dollar/percent threshold
  • ActionCreate controller task in AsanaAsanaAsana
  • OutputEmail escalation to finance leadGmailGmail

What it does

Adds a materiality gate on top of daily reconciliation so only meaningful breaks reach a human. It reads the morning's unexplained-variance total from Postgres, compares it to a configurable dollar and percent threshold, and when either is breached it creates a tracked task and an email escalation so nothing material goes unowned.

When to use it

Use this when small recurring variances are noise but a large unexplained swing is a genuine cash event the controller must investigate the same day. It enforces a clear ownership trail and an audit record for material breaks without alerting on every minor mismatch.

How it works

  1. 1A scheduled trigger runs shortly after the morning reconciliation job finishes.
  2. 2Queries Postgres for the day's total unexplained variance and the largest contributing items.
  3. 3A logic step evaluates the total against the absolute-dollar and percent-of-flow thresholds.
  4. 4If breached, creates an Asana task assigned to the controller with the top variance lines attached.
  5. 5Sends an escalation email to the finance lead summarizing the breach and linking the task.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect PostgresAny Postgres URL — query, write, migrate.
  2. 2
    Connect AsanaTasks, projects, milestones — everywhere.
  3. 3
    Connect GmailRead, draft, send, label.
  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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