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An Accounts Receivable Aging Analysis Playbook scores every open invoice on payment probability, surfaces the customers driving DSO, and recommends the collection strategy that matches each customer's payment pattern.
The Challenge
The standard AR aging report breaks receivables into 30, 60, 90+ day buckets. It describes the present moment. It does not predict which 30-day invoices are heading toward 60, or which 90+ day balances will actually be collected versus written off. The report is read and filed.
Some customers pay 18 days slower than the average without ever crossing into "late". Others pay on time most months but slip in quarters when their own cash is tight. Without modelling per-customer payment patterns, AR teams chase invoices instead of customers.
Most AR teams run the same dunning sequence regardless of customer. The customer who responds to a day-7 reminder gets the same emails as the customer who needs an executive-level call by day 30. Tactics are matched to the invoice age, not to the customer's actual payment behaviour.
How eyko Solves It
An Accounts Receivable Aging Analysis Playbook reads invoice and payment history, customer hierarchy, and contract terms. It scores every open invoice on payment probability, segments customers by historical payment pattern, and recommends collection tactics that match each segment.
The Playbook surfaced $1.8M in receivables over 60 days, of which the payment-prediction model identifies $420K as high collection risk. Customer segment B pays 18 days slower than segment A on average. Historical data shows that automated reminders at day 7 reduce late payments by 34% on segment A but show no measurable effect on segment B, which requires executive contact by day 14.
| Metric | Current | Benchmark | Status |
|---|---|---|---|
| Primary indicator | Flagged | Target | Action needed |
| Secondary indicator | Monitoring | Within range | On track |
| Trend direction | Declining | Stable | Review required |
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FAQ
Everything you need to know about AR Risk by Customer Segment.
Accounts Receivable Aging Analysis is an AI-driven analysis of open invoices and payment history that predicts which invoices will pay late, segments customers by payment behaviour, and recommends the collection strategy that matches each segment. The output is a forward-looking risk view at the invoice level, not a backward-looking bucket report.
The Playbook reads from your ERP or AR system (open invoices, payment history, dispute history), CRM (customer hierarchy, contract terms, segment), and any cash application records. It can also incorporate communication history (dunning sequences sent, payment promises, escalation events) to evaluate which collection tactics have worked on which segments.
The Playbook fits a payment-prediction model against 18 to 24 months of historical invoice and payment data. Inputs include customer segment, invoice size, invoice type, contract terms, prior payment behaviour, and the customer's recent payment patterns. The model returns a payment-probability score for each open invoice with the days-to-pay estimate attached. The output ranks invoices by collection risk weighted by dollar exposure.
Yes. The Playbook clusters customers by historical payment behaviour and recommends a distinct collection motion for each segment: automated reminders for predictable payers, executive contact for relationship-driven payers, and billing review for dispute-prone payers. The output assigns every open invoice to a segment and routes the recommended tactic to the AR team automatically.
Join the enterprises replacing weeks of manual analysis with a single prompt. See what eyko Playbooks can do with your data.
