The Starting Point
The distributor managed relationships with 300+ customers and generated $8 million in annual revenue. Their accounts receivable team worked diligently—sending invoices, tracking payments, following up on overdue accounts.
Yet roughly $75,000 in receivables remained uncollected across dozens of accounts.
Some invoices were only 15-30 days overdue. Others had been outstanding for months. The team treated each as a separate collection problem rather than seeing patterns across the entire customer base.
The AI Analysis
By analyzing payment history and customer behaviour, AI identified patterns the traditional aging report missed:
Pattern 1: Certain small customers consistently underpaid invoices by 5-10%, assuming they could negotiate. The finance team had never noticed the pattern because each instance was small.
Pattern 2: Several larger customers had recent address changes that disrupted their normal payment flow. Invoices were going to old addresses, creating unintentional delays.
Pattern 3: A cluster of invoices across multiple customers was now 90+ days overdue, but no systematic follow-up had occurred beyond standard reminders.
Pattern 4: Certain customers always paid on the same day of the month, suggesting they worked through their accounts payable on a fixed cycle—sending invoices before that cycle increased collection probability.
The Recovery Plan
Using these insights, the company implemented targeted collection strategies:
Underpayment Accounts: The finance team contacted customers to establish explicit payment terms and expectations. Several customers increased their payments once they understood the issue.
Address Issues: Updated customer contact information and resent outstanding invoices. Several payments came immediately after corrected delivery.
Aged Invoices: The accounts receivable team prioritized follow-up on the 90+ day accounts. Personal contact from management recovered 85% of the amount in this category.
Payment Cycle Timing: Adjusted invoice delivery to align with customer payment cycles, reducing future payment delays.
The Results
Within 60 days, the company recovered $62,000 of the $75,000 in outstanding receivables. More importantly, they restructured their collection processes to prevent similar accumulation in the future.
The additional cash flow improved working capital and reduced their reliance on short-term financing.
The Broader Lesson
This case illustrates a key insight: Most uncollected receivables aren't the result of customer dishonesty. They're the result of patterns, communication breakdowns, and forgotten follow-ups. When you see the patterns clearly, recovery becomes possible.
Your accounts receivable data has already recorded all the clues. The question is whether you're looking at the data systematically enough to find them.