Remittance parsing plus deterministic matching now applies the large majority of incoming payments to open invoices automatically — including messy bank-statement and email remittances that used to need manual keying.
Auto-application 60%→92% clears ≈3 days of unapplied cash (≈$41M) into the ledger sooner; ≈$2M/yr yield on cash recognised earlier plus faster, cleaner reconciliation.
Opens your own Claude with the prompt and reference data pre-loaded as text — no upload, no setup. Tailor it live to your own numbers.
Synthetic KokoAI figures — a demo fixture, not audited or a guarantee
Try it
Illustrative demoWorked example of "Cash Application" 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.Capture payment and remittance data from bank files, email and portals.
- 2.Parse remittance detail and normalize references.
- 3.Match payments to open invoices straight-through above a confidence threshold.
- 4.Auto-post matched cash; queue short-pays and unmatched for review.
- 5.Hand off short-pays/deductions to the dispute workflow.
Prompt / agent recipe
Parse the attached remittance and match each payment to the open invoices in the AR ledger. Apply matches with confidence ≥ [threshold]; for partial or unmatched payments, show candidate invoices and the gap, and label likely short-pays vs. on-account.
- Confidence threshold for straight-through posting approved
- Unmatched/short-pay cash held for human review
- Bank reconciliation confirms applied cash
- Audit trail of every match and posting