AI in accounting: reconciliations, payment reminders, closing

AI is not meant to keep the books in place of your teams. It steps in on the tasks that consume time before the accountant’s decision:

• Reconcile bank transactions with entries, and invoices with purchase orders.
• Spot anomalies: amount discrepancies, duplicates, a change in a supplier’s bank details, an invoice with no purchase order.
• Prepare customer payment reminders, taking into account the history and any open disputes.
• Organize the close: task list, missing documents, first analyses of year-over-year variances.
• Answer internal questions: where a supplier’s payment stands, which invoice matches which purchase order.

These uses do not require changing accounting software. AI reads the data where it is, in the ERP, the accounting software, bank statements or email, through connectors approved by the IT department. It works with your rules: tolerance thresholds, chart of accounts, approval workflows.

For each task, AI proposes and documents; the accountant checks, corrects and approves. Our finance page presents these uses for the close, invoices and cash management.

Bank reconciliation

AI compares statement transactions with pending entries, proposes likely matches and explains why: same amount, same reference, same counterparty. Uncertain cases are presented separately. The accountant approves the proposals and handles the exceptions, instead of ticking off every line.

Matching purchase order, receipt and invoice

For supplier invoices, AI checks that the purchase order, the goods receipt and the invoice match: quantities, unit amounts, payment terms. Compliant invoices are presented for approval; the others are flagged with the discrepancy found. The buyer or the accountant makes the call.

Warning signs

Some checks deserve to be systematic, because they protect the company:

• a duplicate invoice, even with a slightly different reference;
• a change in a supplier’s bank details, to be confirmed through another channel before any payment;
• an invoice from an unknown supplier or with no associated purchase order;
• an unusual amount compared with the history.

AI flags; the decision to block or pay remains human, according to your delegation rules.

Reminders are often sent late and in a uniform way, for lack of time. AI can prepare each reminder taking into account the customer’s actual situation:

• History: habitual or occasional late payments, payment promises, previous exchanges.
• Open disputes: a contested invoice is not chased like a forgotten one. AI flags it and instead prepares a check-in with the team concerned.
• Tone suited to the relationship and the stage of the reminder, from a simple notice to a formal demand, the latter still decided by a person.
• Useful documents: copy of the invoice, signed delivery note, account statement.

The accountant or the collections officer reviews, adjusts and sends. The salesperson who covers the account is informed, so the reminder does not disrupt an ongoing negotiation. Payment promises obtained are recorded, and AI prepares the next reminder if the deadline is missed.

The close concentrates many verification and documentation tasks. AI can prepare a good share of them:

• The list of closing tasks, with owners and status.
• Missing documents: invoices not yet received, expense report receipts, up-to-date contracts.
• Proposed period-end adjustments, with supporting documents, submitted to the accountant.
• Variance analysis year over year or against budget, with a first explanation that the financial controller checks.
• The working file for the statutory auditors: documents gathered, reconciliations documented.

A concrete example: variance analysis. AI compares each line item with the previous period and the budget, isolates variances beyond the threshold you have set, then looks in the documents for a possible explanation: a new contract, an exceptional invoice, a change of supplier. The financial controller receives a list of variances already documented, which they confirm or correct before writing their commentary.

Nothing is posted to the books without approval. The point is to spend closing time on analysis rather than on hunting for documents.

• Choose a first process that is frequent and well documented: bank reconciliation or supplier invoice checks are often good candidates.
• Describe the current rules: discrepancy tolerances, approval workflow, signing authority. AI applies your rules; it does not invent them.
• Connect AI to the sources with the IT department: ERP or accounting software, bank statements, purchasing tool. Access is in principle limited to read-only.
• Test on a past period whose outcome you know, to compare AI’s proposals with what was actually done.
• Go live with the team, keeping systematic approval, then measure on your indicators: closing time, invoices with anomalies, customer payment times.
• Extend to payment reminders, then to preparing the close.

If your management tool is a set of spreadsheets or legacy software that cannot be connected, rebuilding it as an AI-ready tool may be a prerequisite. See our in-house ERP use case.

E-invoicing. In France, since September 1, 2026, all companies must be able to receive electronic invoices, and SMEs will have to issue them from September 1, 2027. Large and mid-sized companies have had to issue them since September 1, 2026. Structured invoices make reconciliation easier: now is the time to review your processes.

Segregation of duties. AI must not be able to both propose and approve a payment. Existing delegation rules apply, and the agent has only the rights strictly necessary.

Audit trail. Every AI proposal, every approval and every correction is logged. Your statutory auditors must be able to understand what was done, by whom, and on what basis.

Data. Bank details, customer data, unpublished financial information: choose a tool whose contract rules out training models on your data, with suitable hosting. See our security page.

Review. An explanation of a variance produced by AI can be plausible and wrong. The controller checks it before it is shared.

We map the reconciliation, payment reminder and closing tasks with your finance department and choose the first cases. In hands-on sessions, your accountants build with us the agents that prepare their work. The AI Factory connects AI to your ERP and your bank statements, or rebuilds the management tool that is holding things back, ready for e-invoicing. The code and the data stay with you.