From Data to Action: How Automated Intelligence Is Changing Collections

Most businesses have no shortage of customer data. They know who their customers are, how they pay, when they tend to pay and, in many cases, exactly when a payment goes wrong. The harder question is what to do with all that information—particularly when a customer falls behind.

That makes collections less of a data problem than an action problem.

Automated intelligence can bridge that gap, using customer information to determine what should happen next and creating a more effective, individualized approach to collecting payments. In a PaymentsJournal Podcast, Robyn Burkinshaw, CEO and Founder of Blytz, and Christopher Miller, Lead Analyst of Emerging Payments at Javelin Strategy & Research, discussed how incorporating AI into actionable reminders can enhance the payment experience for customers and businesses alike.

Moving Up from Basic Automation

In payment collections, basic automation typically follows a fixed set of rules: send a reminder on a certain day, make a call when an account becomes past due or retry a payment at a predetermined time.

Automated intelligence takes a different approach. Rather than simply following a schedule, it looks at what is happening with the customer and uses the data a business already has to determine the next best action.

That could mean choosing the right message, channel, timing, tone, or payment option for a particular customer or account. Instead of leaving customer data sitting in a database, automated intelligence turns that information into an active workflow.

The result is a more differentiated experience. Higher-risk accounts can receive a more thoughtful, targeted path to payment, while lower-risk customers can move through a faster, more streamlined self-service experience. In both cases, the approach better reflects what the individual customer actually needs

“It’s different when you’re talking to a customer who’s a day late than when you’re talking to a customer who hasn’t responded in three months,” said Burkinshaw. “Intelligence is going to pick up on those nuances to make the experience better for the customer, and thus make the experience better for the merchant.”

Differentiating Customer Experiences

Consider a customer with variable income. Another generic past-due reminder may not help them make a payment. What they may need instead is flexibility: the ability to pay part today and the rest later, use a different card, pay by ACH, or set a Promise to Pay without having to call during business hours.

“The notion of differentiated and customized experience is commonplace at the high end of the market,” said Miller. “It is what financial services companies talk about all the time in terms of surfacing offers for well-qualified consumers, or analyzing their transactions to see what next thing might be useful to sell them. The same set of technical capabilities should be applied to this particular use case in a way that drives not just incremental gains, but substantial gains in productivity.”

The idea behind the 90/10 rule is that roughly 90% of customers will do what the business wants them to do—make their payments regularly and on time. The remaining 10% are more likely to require additional attention.

Automated intelligence can help businesses keep the 90% moving through a streamlined process while focusing resources on the 10% who need more support. Just as importantly, it can help identify which accounts actually require that attention.

A customer who pays late every Friday but has never missed a payment should be approached differently from someone who has ignored every outreach attempt for three months. Those distinctions are easy to overlook when every account follows the same rules. Automated intelligence can identify those patterns and use them to shape the next best action.

“That’s the shift,” said Burkinshaw. “The future isn’t more reminders, it’s more relevant reminders, and it’s the ability to take immediate action from that reminder.”

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