Webinar Recap: How Conversational AI Transformed a Financial Services Contact Center

By Harry Chang
December 15, 2021

Last week, Replicant Co-Founder and CTO Benjamin Gleitzman was joined by Mike Bowman, Director, Servicing Operations at ECSI for a live discussion about how the financial services company uses contact center analytics in action.

The discussion made one thing clear: analytics in the contact center have never been more important.

2021 changed the way customers think. The pandemic upended every industry, and customers asked more questions than ever about the services they use. Contact centers faced hiring challenges that shook customer satisfaction scores as demand soared and agent availability dwindled.

ECSI – the leading provider of accounts receivable management and campus-based student loan servicing – was a shining example of a contact center getting smart to overcome the challenges of the market.

By using conversational AI to relieve their strained live agents, they also uncovered rich insights about their customers that further helped them improve how they serve them.

Highlights from the webinar can be found below, and the full webinar can be downloaded here.

What challenges lead ECSI to conversational AI?

Bowman also noted the highly cyclical nature of their contact center. “Nothing’s easy about the call volume, our business is very seasonal,” he said.

“There’s very busy times of the year. And then there’s very slow times of the year. And so just with any other business, it’s hard to staff for the huge peaks, and then those valleys in your call volume. We just had inconsistency that we always wrestled with as far as having the right number of people, and that also put a strain on service level.”

Why was Replicant the solution of choice?

What results did ECSI see after deploying Replicant?

“The contact center can dig into these reports, these dashboard reports,” Bowman said, “look at actual caller behavior, get really minute detail on what’s going on in these queues and the Thinking Machine, and then put numbers to it to demonstrate to our product design team and our customer experience team.”