What changed
Classical AI matching plus rules now clears the high-confidence reconciliations straight through, so preparers spend their time only on exceptions — not on ticking and tying lines that already agree.
Try it
Illustrative demoWorked example of "Account Reconciliation Triage" on synthetic data — edit the inputs to tailor it. Edit the inputs to tailor the output — it's baked synthetic data, so nothing leaves your browser until you run it live.
Synthetic demo company (a ~$5B high-growth US AI SaaS) — swap in any name to tailor the output.
What this run should concentrate on.
Workflow
- 1.Ingest sub-ledger and bank/GL balances for the accounts in scope.
- 2.Auto-match transactions above a confidence threshold and mark them reconciled.
- 3.Cluster the unmatched items into break types (timing, missing, duplicate, FX).
- 4.Draft a proposed disposition and supporting note for each break.
- 5.Queue exceptions for preparer action; lock auto-matched items for reviewer sampling.
Prompt / agent recipe
Match the attached sub-ledger lines to the GL/bank lines. Auto-clear pairs with match confidence ≥ [95%]. For everything unmatched, classify the break (timing / missing / duplicate / FX / other), propose a disposition, and explain your reasoning. Never auto-clear below the confidence threshold.
Controls required
- Auto-match confidence threshold approved and monitored
- Reviewer samples a percentage of auto-cleared items
- Segregation of duties preserved (preparer ≠ reviewer)
- Full audit trail of match decisions retained