Finance · Process breakdown
Put routine payment reminders on rails, let AI draft the awkward ones, and keep the difficult conversations with a person.
Chasing overdue payments is where accounts receivable automation pays off first, because most of the work is a cadence: check the ageing list, send the reminder, log the promise, escalate when a promise is broken. Yet accounts receivable automation stops being simple the moment a customer disputes an invoice or a good client hits a rough month. That is why this process is a mix: rules for the cadence, AI for the messages that need context, and a person for anything that touches the relationship. Start with the data. If the ageing list is wrong, every reminder you automate is an apology waiting to happen.
Pull open invoices, due dates and payment status from the accounting system every morning and group them by customer and days overdue. Structured data on a schedule is a rule’s job.
Friendly reminders go out at agreed intervals with the invoice attached and stop automatically when payment lands. Nothing here needs interpretation.
AI drafts the second and third message so it references the earlier reminder, the promise made and the open amount. The credit controller reviews the tone before it goes out.
AI reads the customer’s reply, extracts the promised date or the dispute reason, and proposes a note for the account. A person confirms it before it drives the next step.
A person phones the customers with broken promises, large balances or a relationship worth protecting, and decides on payment plans or escalation.
Automate only the first reminder for one customer segment and one month. Count how many reminders went out, how many were wrong or unwanted, and how many replies needed a person. Add the drafted second reminder only after the first one has run a full cycle without complaints.
Treating collections as a messaging problem. The message is rarely the reason a customer pays late, and a perfect sequence sent about a disputed invoice makes things worse.
If your accounting system already exposes open invoices and payment status, a workflow tool can run the cadence and the reminders, and that is usually enough for a first version. Dedicated accounts receivable automation software makes sense when you need customer portals, card payments or cash application at volume. Either way, the stop conditions and the human escalation path matter more than the product.
State the invoice number, amount, due date and how to pay, in a tone that assumes an oversight rather than bad faith. Each reminder in the dunning process should escalate slightly and reference the previous one. Keep consequences factual and only mention steps you will actually take. AI can draft these variations well, as long as it works from the ledger and a person checks the firmer ones.
At the exceptions: disputes, broken promises, large balances, and any customer where the relationship is worth more than the invoice. A person also owns the decision to escalate, to offer a payment plan, or to write an amount off. Automation should make those moments visible earlier, with the history attached, rather than trying to handle them.
Illustrative workflow guidance by Arcgent. Each business needs its own assessment. No integration or savings claim has been verified for your systems.
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