How AI Helped Radiant Credit Union Grow 60% Without Adding Contact Center Staff

This webinar, title is how AI help Radiant Credit Union grow thirty percent without adding contact center staff.

As a industry, we are obviously trying to grow. And how do we grow without increasing operational cost is top of the mind?

Hello. My name is Eric Whistler. I’ve been with Radiant, like you said, five years. I’ve been in contact centers for over twenty five, in leadership for over twenty three years in the con contact center space. And we’ve got a a nice omnichannel solution here for our membership and really built that with with interface in mind as we as we built out our our AI capabilities within our contact center.

I go by Sri. I’m the cofounder CEO of Interface dot ai.

Come from a credit union family myself and ex Microsoft. As a company, we’ve been around eleven years, headquarter here in California.

You know, we are close to hundred seventy plus employees. We are also a.

We only serve credit unions and community banks.

It’s a platform that’s purpose built just for the just for you. We won best AI awarded American banker.

We also featured InfiniWait as a best AI, mentioned in Gartner, Kuna, Allied, which is our active partner in distributing our solution. We have over a hundred financial institution today, growing rapidly from all the way from three hundred, four hundred million dollars in asset to, close to fifteen to twenty billion dollars in asset.

And what better way to actually see and experience the demo in action than calling into the demo phone line that I have set up for Radiant? So let me go ahead and make a phone call, and I’ll put my phone on speaker.

You can ask for my help with anything. For example, you can say account balance, deposit status, transfer funds, transaction history, or loan payment. What can I help you with today?

Hey. It’s pretty hot, and I’m thinking of buying a boat. Do you have a loan for that?

Radiant Credit Union does offer boat loans with quick online applications, fast approval, and great low rates. I can text you all these details if you’d like.

Can you also tell me what is my checking account balance?

Would you like to use device biometrics for authentication? Thanks. You’re authenticated. Your business checking account ending with seven eight nine zero has an available balance of one thousand dollars and a current balance of one thousand dollars.

The AI agent, Alex, sounds normal and natural just like how a human being does and was able to provide the right kind of information to the member.

Cool part, we take security and compliance very seriously. So the AI agent answers questions only based on the knowledge that it has been made available. In this case, the only knowledge source it has is Radiant’s use member facing website.

Radiant has been using our voice AI solutions since zero nine twenty twenty three, Chat dot ai, since December twenty twenty two. And within Chat dot ai, we have smart discovery and smart transaction.

One of course course that stood out the most was updating an outdated push button IVR and phone banking solution. The phone banking solution that we had was very manual and legacy and wasn’t really supported anymore.

And so we needed some sort of AI solution for self-service during that. Push button IVRs are very complicated and often lead to the the wrong person getting the call, and so we really wanted to meet members where they wanted to be met and making sure that they got to the experts they needed to speak with. Purposely pick the the the number of staff that we would need if we had, interface along with us so we wouldn’t have to grow just because the the grow staff headcount just because the the call volume might increase. We needed if we could find a way to contain those simple calls, we could grow without adding additional headcount.

So we knew that Jack Henry worked well with with Interface. They were a partner recommendation as well. As I said, we were really looking to because we’re this is kind of our first step into AI and you know utilizing that solution. So understanding how it would collaborate and and work in that ecosystem, walked very logically over time and built some strong very strong intents to make sure the the customer experience was not lagging compared to what they they had come from.

It wasn’t so much about the containing the the head count or containing calls. It was about that membership experience and making sure our members had a a self-service solution outside of our business hours. And I think that really helped us choose Interface. Another reason, as I stated, why we chose Interface is during our selection process, understanding their partnership and how they would walk us through getting implementation set up early days.

We’re it’s spreadsheets, as Sri said. It was spreadsheets and kinda understanding step by step on each little thing happened. And so it was very manual, but there it was very purposely responded to as we set up each one of these intents. Now we have the website scraping, so anything that we update on our website, we can notify if need to refresh right away. Otherwise, it it will refresh as we make updates to our system. It’s really helped out.

So this is a total call voice calls and every automation rate. So the voice calls are maybe around thirty five thousand per month, Eric?

Yes.

Yeah. And we are running at seventy five percent automation.

We like it when Ray’s available. We I I don’t know if anybody would experience some of the Microsoft outages back a year ago, but when the bot went down, we had callers asking where the bot was. So that really spoke to us on that and our associates that the customers do like the capabilities and the quickness of getting some of those simple answers that that you can get with the bot. So I I think the big thing is, when you roll this out is making sure that the associates have complete buy in, and they they trust that that they in the the bot itself, we got them involved in the UAT testing, making sure that they could understand the, intents that we were built.

We’re not trying to deflect calls. We’re trying to contain calls that, memberships can help self serve with our previous growth as Radiant before we merge. We hope that over time our First Coast membership will adopt as well as our Radiant members have and they will be able to self serve and we’ll be able to handle some of those after hours calls and self serve calls for their membership without having to grow much more headcount based on just solely the number of members that we’ve added. Nobody wants the the the specialist to get, in our case, a balance inquiry.

That should be your new hires. Right? So when when the bot kinda recognize it, it’s not the customer pressing a prompt and saying balance inquiry. It’s they’ve said balance inquiry and therefore, they end up with that associate that can do that very simplified task.

So, service level is definitely impacted because the customer is getting to the right person.

We felt it was around four FTE, which was about twenty five percent of our staff that we were expecting based on call volumes prior to interface. The call volumes have may may have increased the interface and the the bot itself, but as far as calls coming into our contact center, we have not seen a significant jump to need additional staff during our growth. It’s really containing those simplified calls. It did help us having to add extra headcount.

And thank you all for attending. I hope you enjoyed the the discussion here, and you are ready to take the next step in your AI journey, which is, again, book a demo with us, and we’ll go from there. Thank you so much.