Debt recovery and collection looks quite different in 2022 than it did 10 years, five years, even just a year ago. There are new channels to reach consumers, larger data sets to analyze, complex regulations that can vary state by state, and so much more.

So, when it comes to deciding the best way to engage consumers and effectively recover debt, has your strategy evolved to keep up? Machine learning, artificial intelligence, data science—these terms are thrown around a lot, and for good reason.

A recent survey of lenders found 69% reported that machine learning will become a differentiator for financial services by 2024, and the survey found that lenders are already seeing the effects of using machine learning in their strategies today: 86% saw improved data analytics and 77% have seen improved productivity by using this technology.

A debt collection-focused machine learning model is showing that it can evolve and improve collection efficiencies at different stages of the collection process. But what are the real differences between a machine learning strategy versus the traditional status quo with its seemingly tried and true call-and-collect and email blast methods?

From delivering a better experience in line with what members expect from credit unions to streamlining communications designed to constantly learn from every interaction, machine learning has gone from a “nice to have” to a “must have” for collection efforts. But how does it tactically improve the experience for both lenders and members?

Answers to these questions and more are all laid out in layman’s terms in TrueAccord’s latest eBook, “Decoding Machine Learning for Credit Union Debt Recovery and Collection,” available for download now.

This highly visual guide is designed to cut through the jargon and help you understand the basics of how machine learning is applied in collections. Straightforward definitions, clear diagrams, and bottom line benefits make this eBook your at-a-glance guide to machine learning in debt collection for credit unions.

Discover how machine learning-powered collection strategy drives overall improved performance, better member experience, and the more effective recovery of delinquent funds—without implementing more manual processes or adding headcount to your team.

Visit trueaccord.com to view the eBook and the rest of TrueAccord’s offerings.