Supercharging Agent Productivity with AI

Artificial Intelligence (AI) means different things to different people. What it lacks in its finesse with human interactions, it makes up for in speed. Credit collection and management agencies are engaging with AI to leverage its efficiency in handling industry-specific tasks. Matt Maloney, President of FFAM360 Alliance Group of Companies, and Shantanu Gangal, CEO and founder of Prodigal, offered their insights on a ACA podcast into how AI can supercharge productivity in at a collection agency.

The full podcast can be found here. Key takeaways from the ACA podcast are summarized below:

Opportunities for AI

Live agents connecting with consumers are the heartbeat of any collections organization. Yet, humans have their limitations. They can only work eight hours each day. They become tired and require breaks during their shifts. “AI can do a lot of consistent work without tiring, making 24/7work rotations possible,” said Gangal.

AI is not a novel concept at FFAM360. Maloney said his group began exploring AI and the use of different sub-groups for the better part of six years. “We’ve really invested heavily in it in the last 24 to 36 months. To keep it from becoming overwhelming, you’ve got to pick one lane, build a car to drive in that lane so that you can learn from it, and then expand.”

Leveraging AI as a virtual assistant of sorts is one of the leading ways debt collectors maximize the efficiency of the live agents they are relying on to drive revenue. “There’s no secret to this,” said Maloney.“Most organizations see their agents are spending most of their time in the after-call wrap-up note-taking. That’s been, industry-wide, a source of constant work.”

Gangal concurred, estimating agents spend 2 to 2.5 hours post-call posting notes about the account, scheduling follow-up reminders, and posting payments. “You are leaving pennies on the floor. It adds up to $8,000 to $10,000 per year, per agent.” Since speaking with consumers is where live agents shine, Gangal suggested AI could handle completing the post-call wrap-up tasks.

Measuring Agent Productivity

The productivity of live agents is correlated with revenue. During peak seasons, like the upcoming 2021 tax season, it is a huge risk. There are several ways organizations measure agent productivity. Call times, the right party connects, conversion rates, and average payment per call are a few of them.

“People are the heart of any collective effort,” said Gangal. “They are also the biggest cost.” Organizations must figure out how to manage that cost while splitting out the revenue they are bringing in across the day.

Maloney said his organization has a specific metric divided out by type and orientation, asset class, business, and aging of accounts receivable. The expectation and metric used to measure call wrap times are distinctly different, depending on the client.

Using AI to Boost Productivity

Gangal said the best use of AI is to help reduce the call wrap-up time for live agents. He likened it to a doctor’s office visit, where you may be there for a full hour but only interact with the doctor for 15minutes. “That is obviously the most important 15 minutes of that time. But the doctor is not spending the whole hour with you. Wrap-up time for agents should be handled similarly.” A small part of the interaction is human-to-human, he said. The follow-up time annotating what has happened should be left to a machine, which can more efficiently manage it.

Maloney said his organization is exploring AI in a live setting. They have found it works best with large volumes of accounts to create efficiencies for agents. “Every single day, our accounts are being reprioritized through an automated workflow with the application of artificially-intelligent analytics that is driving that.”

Measuring the gains is a little more subjective, Gangal added. Turning average agents into top performers are probably one of the best goalposts for evaluation. “How can technology minimize the differences in the skill level of agents? Why do certain agents do better than others? AI can analyze and streamline their methods to determine areas of focus to help them improve.”

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