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The AI in collections outlook for 2024

What’s your team doing with AI? 

“Everyone’s looking at leveraging AI. But there’s a little nervousness in that space,” a consumer finance leader told us recently.

TransUnion’s report on the state of 3rd-party collections in 2023 supports both the interest and the anxiety.

As with all industries, artificial intelligence (AI)- or machine learning (ML)-based technologies are expected to have a significant impact going forward. 
Only 11% of companies were currently using AI/ML-based technology across their enterprises. 
However, in total, 60% of companies were somewhere along the deployment path to use AI/ML-based technology, whether it was considering it (40%) or in the process of developing or deploying it (8%). 
The top three uses of AI/ML-based technology by companies on the deployment path were to predict payment outcomes (e.g., willingness or ability to pay), augment the self-service platform (e.g., virtual negotiators), and segment and profile customers for various workflows.

Space for AI in collections

As the pioneer of consumer finance intelligence, we talk to teams across the industry, from agencies to debt buyers to internal collections departments, and that squares with what we’re hearing.

The top three AI use cases we’re hearing interest in for 2024 are:

  1. Determining which customers are most likely to pay for use in account prioritization
  2. Evaluating the right day, time, frequency, messaging, and channel(s) for outreach strategy
  3. Analyzing agent performance to pinpoint behaviors that drive success - and the ones that don’t

The list of possibilities doesn’t stop there, of course. Every question you’ve wanted answers to, or every problem that was beyond human ability to analyze or technology to solve has new potential with AI.

What’s stopping collections teams from using AI

With the CFPB’s ever-increasing regulatory attention and judgments against agencies in 2023, as well as the importance of positive compliance practices for business and consumer relationships, the leeriness described by the leader we quoted above is surprisingly common.

In fact, TransUnion’s report identified 40% of 3rd-party agencies who weren’t considering using AI or machine learning at all.

Why not? It’s different for everyone, but a few common reasons include:

  • Security/regulatory compliance questions
  • Potential costs
  • Not understanding potential uses
  • Lack of resources or expertise to build or investigate
  • Concern about whether solutions are appropriate for company size

Questions to ask about incorporating AI in 2024

All of those reasons for feeling skittish about adopting AI for a collections team are valid.

The problem is, AI tools are not going to be optional. Collections businesses have a high expected failure rate, and mergers are continuing to increase.

As Scott Hamilton puts it:

"If you don't have AI solutions in place, you are going to lose your business."

But there are answers to all your concerns.

So here’s a quick list of questions to ask your team, your colleagues, and providers:

  1. What one piece of information could AI reveal that would transform the way we do business?
  2. Does a solution exist to find that information?
  3. What are the first places other teams are putting AI into place?
  4. How is this AI trained to address collections issues?
  5. How does this AI guard against hallucinations and issues of bias?
  6. What size does my company need to be to see results from AI?
  7. What knowledge do we need to effectively implement AI?

Need more guidance?

We'll be at RMAI in Vegas in a few weeks - click the image below to schedule a time to chat about it.