Finance / 5 min read

Invoices, purchase orders and delivery records: using AI to identify discrepancies

Prepare invoice checks against orders and receipts, covering quantities, prices, tolerances and missing records, with a worked discrepancy example.

You can assess AI for collecting invoices and related records, preparing quantity and price comparisons, and flagging differences against agreed rules. A useful output shows sources and exceptions; it does not approve the invoice or payment. For services, use the evidence required by the agreement rather than assuming a goods receipt exists.

Ask for an explained difference

Opening three documents and finding the same reference is preparation work. Deciding whether undelivered goods can be invoiced, or whether a different price was agreed, needs the context of the purchase. To delegate the first step while retaining the second, ask for a comparison with sources, applied rules and points requiring review.

In Microsoft Dynamics 365 Finance documentation, three-way matching compares invoice prices with purchase orders and invoice quantities with selected product receipts. Tolerances depend on configuration. This describes that system's method; it does not establish an available Digital Employee connector. Source: Microsoft, invoice matching.

The assessment should start with your documents: entity, supplier, order, lines and period. The guide to finance tasks you could delegate helps you choose an initial scope. Here, we follow an invoice check in detail.

One order, a partial delivery and an invoice

This illustrative example uses entirely fictitious data, in EUR, excluding tax and with no discounts or additional charges. Company Alpha purchases the same component X1 throughout. The delivery record documents the physical delivery in this example; we do not assume it alone confirms acceptance or the quality of the goods. It is not presented as a legal equivalent of any particular national delivery document.

Scroll the table horizontally to read every column.

Fictitious records available when the check is prepared
SourceQuantityUnit priceBasis for comparison
Purchase order PO-240, line 1120 unitsEUR 25.00120 × 25 = EUR 3,000.00 ordered.
Delivery record D-81, line 180 units deliveredNot statedPartial delivery against PO-240; 80 × 25 = EUR 2,000.00 at the order price.
Invoice F-610, line 1100 unitsEUR 26.00100 × 26 = EUR 2,600.00 invoiced.

The comparison identifies two differences: 100 − 80 = 20 invoiced units beyond the documented delivery, and 26 − 25 = EUR 1.00 extra per unit. The gap between the invoice and the delivery valued at the order price is EUR 600.00: 20 × 25 = EUR 500.00 for quantity, plus 100 × 1 = EUR 100.00 for price. Do not add these differences to the total again.

The 40 units still to be delivered against the order are different from the 20 invoiced units beyond the available delivery record. They answer different questions. Nor does EUR 2,000.00 automatically become an amount authorised for payment: purchasing terms, further receipts and approvals still need checking.

What the reviewer should receive

For this example, we use an illustrative rule: the price must equal the order price, and the invoiced quantity must not exceed the documented receipt. This is not a recommended tolerance for every business. A useful output could look like this:

Subject and sources
Company Alpha, component X1; F-610/line 1 compared with PO-240/line 1 and D-81/line 1.
Result
Review required: quantity difference of 20 units; price difference of EUR 1.00 per unit. No conclusion about error or fraud.
Missing evidence
Any further delivery and authorisation for the price change.
Owners
Goods receiving team for the receipt; procurement for the price; accounts payable for the invoice review.
Next step
Request the missing evidence and reassess the comparison. This output authorises neither a posting nor a payment.

Define rules at line level

Before comparing documents, establish how to recognise the same item, unit of measure and reference. Ten packs are not ten individual items if the order uses packs of twelve: the conversion must come from an authorised source. Do not assign two similar descriptions the same item code without a rule that can be checked.

Agree which differences need review, who approves tolerances and their calculation basis: unit price, quantity or line total. Keep tax, discounts and additional charges distinct; comparing a gross amount with a net amount produces a difference without a useful basis. The result should identify the rule version applied.

Use an explicit status for missing records. “Purchase order unavailable” does not mean “invoice incorrect”. Preparation can continue for fields that can be checked, while leaving open those that need a source.

Cases that change the comparison

  • Partial deliveries: consider the relevant receipts and quantities already invoiced. Avoid using the same receipt to support multiple invoices.
  • Credit notes: identify the invoice and lines they relate to. An available credit note does not automatically offset any difference from the same supplier.
  • Possible duplicates: the same invoice number, supplier and amount warrant checking, including whether they represent copies or corrected documents. Do not delete records or permanently block a supplier based on similarity alone.
  • Services: there may be no goods receipt. Depending on the agreement, use the service period, progress evidence or confirmation from the responsible person. Do not invent a receipt document to complete the pattern.

Keep three decisions separate

Identifying a discrepancy, approving its accounting treatment and authorising payment are distinct steps. Define who can release each step and which evidence they need, using the guide to controls and approvals. AI does not authorise payments or changes to bank details.

If the original terms are difficult to reconstruct, improve the earlier supplier quotation comparison by retaining exclusions and agreed conditions. To assess this work within the service, start with Digital Employee for finance teams and an anonymised sample containing complete and incomplete cases. Measure the time reviewers need to resolve an exception, as well as how many lines are compared.

Sources and further reading

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