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As of 13 August 2026, AI can identify unpaid sales invoices.
This still needs a person who signs their name to it.
Can you do it?
15 minutesto a draft.
30 minutesto something you’d act on.
Cost, all in£0
Skill neededchat-fluent
Who has to check ityou
What the alternative costsA human bookkeeper remains the alternative, but no price is stated in the supplied tool data.
If this goes wrong: you chase a customer who has paid or overlook a genuine debt, causing avoidable collection work and possible damage to the business relationship.
What to actually do
Hand it to a person
The route this page recommends
A person who owns the outcome does this end to end, worth it when the failure is dear.
Use a tool built for this
Second choiceDo it yourself
The distant thirdA chat interface, chat-fluent skill, and roughly 30 minutes until you can act on the result.
How to actually do it
- Export the current sales invoice list from your accounting system, including invoice number, customer, invoice date, due date, total, credit notes and current status.
- Export the matching payment or bank transaction period, including transaction date, amount, reference, payer and any invoice number in the bank reference.
- Export separate records for credit notes, refunds, disputed invoices and known customer-account transfers.
- Remove unrelated personal bank data and paste the three datasets into the prompt in clearly labelled sections.
- Ask the model to produce the status table and exception list using the exact matching rules in the prompt.
- Compare every item marked apparently unpaid or partly paid with the original invoice, the accounting ledger and the bank transaction export, then correct any unallocated or wrongly matched payment.
- Send only the verified list to the person responsible for credit control, and keep disputed or cannot determine items out of automated chasing.
Prompt
Identify which sales invoices appear unpaid from the records below. Treat an invoice as paid only when the payment can be matched to the invoice number or to a clearly matching customer, amount and date. Account for partial payments, duplicate payments, credit notes, refunds, overpayments and payments that cannot be allocated. Do not assume that an unmatched bank receipt is unpaid revenue. Return a table with invoice number, customer, invoice date, due date, invoice total, matched payments, credit notes, balance apparently outstanding, status, and the evidence for the status. Use these statuses only: paid, partly paid, apparently unpaid, disputed or cannot determine. List every exception separately. Do not invent or infer missing figures. State which records you used and ask for any missing fields needed to improve the matching. These are UK business records, so keep the analysis to bookkeeping and do not give tax or legal conclusions. Invoice export: [PASTE INVOICE EXPORT] Payment or bank transaction export: [PASTE PAYMENT EXPORT] Credit notes, refunds and disputed invoices: [PASTE RELEVANT RECORDS]
Open it prefilled in ChatGPT or Claude, or copy it into Gemini, which takes no prefill link.
What it gets wrong
- It cannot know that an unallocated payment belongs to an invoice when the records do not contain a reliable reference.
- It cannot resolve whether a credit note, refund, dispute or customer-account transfer should reduce the amount owed without your business context.
- It can produce a neat table from duplicated, incomplete or inconsistent exports while hiding a data-quality problem.
- It cannot take responsibility for contacting a customer or deciding whether a debt is genuinely overdue.
- It does not replace the accountant or bookkeeper who investigates unusual balances and prepares the accounts.
Even on a YES, the friction has a name: judgement under ambiguity, verification cost and stakes of error.
How we scored this
Five axes, each scored nought to two by hand: ten means AI carries the task cleanly, and the thresholds that turn a total into YES, PARTLY or NO are published in the methodology. Each axis name links to its definition.
| Axis | Score (0–2) |
|---|---|
| Output | 2 |
| Inputs | 2 |
| Verification | 1 |
| Liability | 1 |
| Effort delta | 2 |
| Total | 8 / 10 |
The methodology and its thresholds are published in full.
FAQ
- Can AI tell me which invoices have not been paid?
- Yes, if you provide an invoice export and matching payment or bank records. It can match references and amounts, flag apparent outstanding balances and separate uncertain cases, but you must check exceptions such as credit notes and unallocated payments.
- Can ChatGPT reconcile unpaid invoices?
- It can help compare pasted or uploaded invoice and payment data, but it is not connected to your accounting system unless you provide the records. Use it to create a proposed list, then check that list against the ledger and bank transactions before chasing customers.
- What information does AI need to find unpaid invoices?
- Give it invoice numbers, customer names, invoice dates, due dates, totals and credit notes, together with payment dates, amounts and references. Include partial payments, refunds, disputes and unmatched receipts so it does not mistake an allocation problem for a debt.
- Is it safe to use AI to identify unpaid invoices?
- It is suitable for a checked working list, not as an unattended decision about who to chase. This is not professional advice, and a serious or disputed case needs your accountant or bookkeeper to investigate it.
Nearby answers
Assessed by gpt-5.6-luna (gpt-5.6-luna) on 2026-08-13, second-checked by an independent model. Wrong somewhere? Email [email protected] and it gets re-checked.
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