Chapter 1
Collecting with context: Data is your compass
Let the numbers speak for themselves
First thing’s first. Getting collections right starts with understanding. The more visibility you have into your customers’ behaviors, preferences and pain points, the better you can tweak your approach — and that starts with data. Whether it’s call transcripts, payment history, channel preferences or risk scores, the insights are there. It’s just a matter of making them work for you.
The smartest collections strategies are powered by AI automation and analytics. According to McKinsey, companies using AI in collections have seen a 10% improvement in collection rates, 40% reduction in cost per collection, 30% increase in customer satisfaction, and a 40% drop in operational expenses.1 Not only does data uncover hidden patterns, but it also helps teams spot friction points before they turn into missed payments. This allows businesses to act faster and with more empathy, boosting success while keeping the customer experience intact.
3 main use cases debt collection companies have focused their AI and machine learning efforts on:
> Predict and segment accounts
> Predict payment outcomes
> Self-service/virtual2
What that looks like in action:
Use speech and text analytics to uncover common objections or confusion points during collections conversations.
Improve data accuracy early to reduce failed contact attempts and frustration.
Automate reminders and outbound messages based on individual behavior or preferences.
Tap into real-time insights to prevent errors and guide next-best actions.
Real-world results
Using analytics to boost PTP and collection rates
One leading motorcycle brand turned to Foundever to enhance its collections process using interaction analytics.
The goal was to build a collections architecture that could: • Analyze Promise to Pay (PTP) interactions to discern opportunities for setting up scheduled payments • Differentiate between instances when agents schedule a payment directly versus when they arrange a PTP • Drive agent adherence towards scheduled payments • Boost total collections by enhancing scheduled payment commitments through targeted, alert-driven strategies
The results
increase in PTPs (66% to 72%)
increase in collections ($3M vs. $2.3M)
The goal is data-backed empathy
It’s easy to assume automation and analytics create distance in customer interactions, but the opposite is true. When used well, data helps personalize outreach, avoid unnecessary friction and make the collections process feel less like a transaction and more like a conversation. And that’s a win for both sides.
1 - McKinsey, “The promise of generative AI for credit customer assistance,” mckinsey.com.
2 - TransUnion, “Debt collection industry annual report,” transunion.com.
Ebook
Humanizing CX in collections: How to balance empathy and efficiency
