Was this payment allocated correctly?
A matching amount is not proof of the right invoice. Wrong allocations surface weeks later — as a reminder to a customer who already paid, or as a dispute. Build your own allocation for three fictional payments and check it against the evidence.
Allocate the payment. Then see if the evidence agrees.
Four checks run on every change: amounts, references, the remittance advice, and payment terms. Change the allocation, the payment date or the evidence to see a different outcome.
Which matching rule should you trust?
The same four checks, applied to the same three fictional payments under three common policies — with the evidence as it arrived.
| Fictional policy | Payments 1 · 2 · 3 | Posted, verified | Posted on weak evidence | Held for a person | Manual workload | Main risk |
|---|
Found in evidence Three fictional payments — not an automation rate or a benchmark. Your own payment history decides which policy fits.
How a recommendation could read
If your own matching history shows amount-only matches conflicting with remittances, then a controlled pilot of policy B on one customer segment could test whether fewer wrong postings justify the extra review time.
Three examples do not show that any policy is best. Changes to matching rules need approval from the responsible finance managers and run within your existing controls.
Keeping the numbers honest
- Matching amount ≠ correct allocation.
- Suggested outcome ≠ automatic posting. A person decides.
- Three fictional payments ≠ a validated automation rate.
- Rule-based checks ≠ AI decision-making.
- Bank statements and incoming payments
- Remittance advices
- Open items at the time of matching
- Matching proposals and manual corrections
- Dispute and deduction logs
Is this decision worth checking in your organisation?
A 20-minute conversation is enough to find out whether it is worth a closer look.