Traditional accounts receivable works like this: you send an invoice, wait for the due date, notice it’s overdue, then start chasing. You’re always reacting to a problem that’s already happened.
But what if you could see late payments coming before the invoice even became overdue?
From Reactive to Proactive AR
Recent advances in AI have made predictive accounts receivable a reality. According to Forrester’s latest research on AR automation, machine learning models can now forecast payment behaviour with accuracy rates above 90%.
These systems analyse patterns that humans simply can’t process at scale:
- Historical payment behaviour: How long does this customer typically take to pay? Do they respond to first reminders or need multiple follow-ups?
- Invoice characteristics: Are larger invoices paid slower? Does payment timing correlate with time of month or year?
- Communication patterns: Has recent correspondence suggested cash flow issues or disputes?
- External signals: Industry trends, economic conditions, and other factors that might affect payment timing
The result is a fundamental shift in how AR can operate. Instead of the same follow-up process for every overdue invoice, you can apply the right approach at the right time for each customer.
What Predictive AR Looks Like in Practice
Consider two invoices that both went out last week:
Customer A has a perfect payment history. They’ve paid every invoice within 5 days of the due date for three years. The AI knows this invoice will almost certainly be paid on time. Result: no premature follow-up needed.
Customer B has been paying later each quarter. Their last three invoices averaged 18 days overdue. The AI recognises this pattern and suggests proactive outreach before the due date to confirm receipt and remind of payment terms.
This isn’t about being aggressive with late payers. It’s about being smart with your time and maintaining relationships. Why chase a reliable customer unnecessarily? Why wait until an invoice is three weeks overdue when the pattern was predictable?
The Right Message at the Right Time
Predictive AR doesn’t just tell you which invoices might be late. It helps determine what to say and when to say it.
An AI that understands your customer’s payment patterns can:
- Time follow-ups appropriately: Some customers respond best on the first reminder. Others need the third. Why guess?
- Adjust communication tone: A customer with a strong payment history who’s running late might need a gentle check-in. A chronic late payer might need firmer language.
- Identify the real issues: If an invoice is stuck because of a dispute or missing information, early identification means faster resolution.
Applying This to Your Business
Aiden uses AI to understand your customers’ payment behaviour and communication history. Instead of sending generic reminders on a fixed schedule, it adapts its approach based on what’s likely to work for each customer.
The goal isn’t just to chase invoices more efficiently. It’s to get you paid faster while maintaining the customer relationships you’ve worked to build.
If you’re still treating every overdue invoice the same way, you’re leaving money on the table and wasting time on approaches that don’t work.