How Agentic AI Is Improving Efficiency Ratios at Navigator and Red Rocks Credit Union

My name is Linda LaFortune. I’m the director of learning and client support here at CU Insight and your host for today’s event. We have a lot of great information to get to, and we’ll be getting started in just a couple of minutes. First, just a couple of quick housekeeping items.

Today’s session is being recorded, and you’ll receive a link to the recording by the end of this week. And also, our speakers today are more than happy to answer any questions you may have, so please feel free to ask those in the Q and A box, which you will see in your menu bar, at any point during the presentation, and we do have time for those allotted at the end.

So that is all of the housekeeping items. So I will start with us going with our agenda for today. We will first learn a little bit about Interface AI.

We will then have our panel discussion with our credit union professionals joining us and finishing up with that q and a session for any questions you may have.

So with that, I am happy to introduce the CEO and cofounder of Interface AI, Srinivas Njay, and he’s gonna get us started with some information.

Thank you, Linda. Appreciate appreciate everyone joining. Thank you, and good morning, good afternoon to everyone. I I go by Shri. I’m the cofounder CEO of Interface dot ai.

You know, a little bit about myself. I actually come from a a credit union family myself. My father scaled a credit union to couple of billion, and I was also, previously at Microsoft, part of their AI research lab, and, you know, got, both my personal professional experience, combined to start Interface dot ai. We’ve been around for eleven years now.

I I feel, old to say that.

It has it’s been, twenty fifteen. We started it we started, you know, this, interface AI focused on offering AI solutions to exclusively for credit unions and banking before AI was a a cool thing. We’ve been doing this for a long time.

You know, a big part of the leadership, and some of our employees are based in California. That’s our HQ. But overall, we’re two hundred people strong. We’re also a Q. So what Interface AI does is we’re a intelligent banking platform purpose built for financial institutions like yourself.

We serve over hundred financial institutions or three hundred and fifty AI deployments with multiple products these financial institutions using. We’ve been featured in Gartner as the best AI vendor for credit unions and community banks, featured in, you know, Acuna, which is, credit, you know, America now, Allied Solution. We won many awards at Finowate, and American Banker is the best AI for the financial institutions.

You know, a little bit about my cofounder, Bruce. Bruce was the inventor of billing invoice. He built the first world’s first ever billing invoice company before joining Interface, scale it up to several, you know, hundreds of millions of dollars of revenue.

And he joined in me in this journey to build Interface AI in twenty fifteen.

You know, that’s a quick introduction to Interface AI. And, Linda, if you go to the next slide real quick, please.

These are all the solutions we offer.

You know, we wanna be your one stop shop AI partner across various different challenges as a in as a industry we are solving together. I deeply believe AI is going to solve lot of our industry problems, either it’s data silos or, you know, you know, generational churn, or it could be about, you know, growth and wallet share. And there’s just some I’m gonna call liquidity. We’re all, thinking about increasing liquidity as an industry now. So there is so many challenges industry has, and, we have, solutions that address most of those top industry challenges through AI first approach.

You know, pretty much, as you can see on the left side on the right side, there’s a voice AI, chat AI, largely member facing AI agents that has ability to automate in inbound incoming calls and, you know, take that interactions to, you know, to next level by using those interactions to be able to sell a product or product financial insight that can drive growth for you. Taking those service interactions to driving growth is what chat and voice AI does. And the employee AI is for the remainder of the, you know, calls and chats that AI couldn’t automate, the employee arguments. So when the caller chat hands over to an agent, a human agent, employee AI assist them, you know, finding policy and procedure quickly, or even taking actions and calling APIs to complete an action so your agents doesn’t have to switch between, like, ten different application.

And it even has a ability to coach them to be able to drive growth for you. It’ll coach them when to sell the right products and services. And we have seen interesting ways our our customers use employee AI. While we build this for frontline staff, now it has been used across their entire credit union.

Either it is a a loan officer or a a CEO of a credit union using that to get their data and answers questions to their answers to their questions.

And on the on the if we’re coming to the right side, the smart collection, which is our new product we launched recently, where AI has ability to do outbound call, you know, and chat and and text message and email to drive collections in an autonomous way.

AI automatically does a, you know, switching between the channels. It’s multichannel agentic solution.

It follows all the, you know, you know, regulations in terms of ensuring how what is the time of the day you call, how often you call. So you don’t have your employees don’t have to worry about a lot of regulations around collection that it could make you easily liable if not followed. You have AI that follows all the rules to drive collections, especially for early delinquency. It has been very, effective.

And then, you know, OLBGPT, this is our online mobile banking replacement. This is a fully agentic solution that is fully AI first online mobile banking. We’re going live with the Credit Union this this year with with the Credit Union, which is replacing your q two online banking with a completely AI first online banking. You know, it’s a it is you know, intelligent automates a request and, you know, drives growth during the conversation.

It’s pretty exciting. Software is going from being a convenience to driving business.

You know? Our OLBGPT is a great example. It’s like it’s like a bank GPT. You know? It’s charge GPT for but for banks and credit unions, it what it does.

Very excited about that. And the AI operator is our product that is basically AI first contact center system.

You know you know, pretty much it it has capability to enable your staff to multitask.

You know, typically, you know, your agent your human agent take one call at a time or a a few chats at a time. With, AI first, context in the system, we built built out an AI system that can actually enable your staff to do twenty, thirty calls at a time, twenty, thirty chats at a time, with AI doing most of the work, but bringing them in where exactly AI gets stuck. Right? So so those are different solutions we have and lots of integrations.

You know, we also have a lot of fraud prevention AI that helps with combating fraud either by empowering your staff or, you know, empowering your members and customers directly. This is kind of what we call a bank GPD platform that has ability to drive, you know, increase improve your member experience or drive growth or drive, you know, efficiencies and and and whatnot. So those are, like, offering from Interface AI today. So very excited to talk about some of these with some of our customers.

Alright. So with that, let me move us here into some more introductions for our speakers today. So joining us for this upcoming panel is Crystal Brown, senior director of IT at Navigator Credit Union, and Josh Henderson, senior vice president of IT at Red Rocks Credit Union. So let me bring them on camera with us.

There we go. Alright. So welcome to all of you. We’re so happy to have everyone here today. And, of course, Sri is staying with us for this panel discussion so we can get input and aspects from all sides of the fence here. So let me move into our first question.

I just need to rearrange my screens here. Okay.

So, Sri, we’re gonna start with you on this one, and we’re starting off with what makes AgenTik AI fundamentally different from the first generation generation chatbots and IVR systems credit unions have used in the past, and why does that difference matter right now? So we’ll start with Sri, and then roll through Crystal and Josh for those.

Wonderful. So I I think I look at this from three different, lenses. Right? Number one, what is the member experience?

Number two, what is the credit union experience in managing the system? And number three is, you know, the risk and compliance side of things. Those are three different lenses and how you look. Agentic systems are different compared to traditional chatbots and, you know, IVR systems.

You know, if you think about the first lens, which is members, you know, members in with agentic systems, member experience in AI that is very fluid. It can you know, it it is very knowledgeable.

You know, usually, the, agentic AI systems, it learns everything from your website or documents you upload. It’s very knowledgeable in answering, questions about your promotions or, you know, interest rates, or, you know, if if they have a a broad question or a problem, it is able to, be consultative. Right? If they could come they could come in and say, you know what?

I have credit card debt problem. How do you think I should solve it? Then in order to come with a specific need, they can ask a then they can ask the problem they’re facing, and then the AI can find the solution for them. That’s the kind of member experience with the agent AI.

It’s consultative, and it’s very knowledgeable and and things like that. And it’s also continuously learning. So that’s that’s what members expect today, your AI systems too, and agent AI delivers on that.

And it also has ability from the member’s point of view to execute transactions.

You know, it could be simple transactions like checking recent tran recent transactions to all the way even doing fund transfer, wire transfers, or paying auto loan, paying off your auto loan. It it has a ability to kind of do that end to end, and, you know, drive insights and product recommendation while doing that. Right? So if someone calling in to set up an auto loan payment, it doesn’t just stop there.

Agentic AI systems are, very advanced where your members will feel, during a conversation, you know, when they come in to set up an auto loan, it probably recommends them an extended warranty. Right? So, you know, because it recognizes there is a need for the member for a product like that. That’s kind of the member experience lens.

But if you look at the credit union lens, what agent maintaining agent AI system feels like, you know, compared to the traditional chatbot, they’re not sitting there and scripting responses. That’s number one number one thing. Right? So, you know, that’s the part of agentic AI.

But when you look at in chatbots and previous generation AI systems, you literally had to still it maintaining AI didn’t feel like AI, honestly. You had to sit and script the responses. And we have been there ourself a few years back. And some of our customers had to do that, but now the world has changed so fast.

You know, you just point the AI to the knowledge. You tell the AI what to do, what not to do. It can figure it out and drive the outcomes for you.

And, you know, pretty much from a credit union lens of view, maintaining an agent agentic system is is training it it’s like training your best employee. Right? You know?

Or onboarding your best employee. Right? You’re not sitting and, scripting or, you know, at, you know, assisting them in every small thing. Right?

So that’s kind of the best way to kinda think about, agent AI systems. And from a compliance and risk perspective, you know, the third lens, you know, pretty much the old generation systems, were, you know, were challenging. Right? So, because it it it was a compromise to offer, old generation AI, in terms of member experience.

There was a certain degree of compromise. But in terms of compliance, it it it it was okay, but, you know, it it couldn’t detect the pattern of fraud, for example. Right? Or it couldn’t do biometrics to authenticate better.

But agentic systems are far more capable in detecting fraud. Right? Like, they usually have AI based biometric authentications that will enable to prevent fraud better, and they do not, know, make things up. Right?

Agenda systems that are built for our industry in a careful way, you can get the benefits of of it, but and also not the disadvantages of typically AI system, which is typically AI systems make things up, hallucinate, you know, but the right agentic systems would solve for those problems. Those are, like, three lenses I look at. Members and credit union staff maintenance and then the compliance risk. Often, is a misunderstanding or a misconception.

Agentic systems can hallucinate, but that’s not accurate. Right? If it is built in the right way, it can solve those problems. Right?

So Perfect.

And I think Crystal is gonna jump in next.

Yep. I think she covered a lot of it, but but for us, with a with a background in IT, and not having had an older AI system, one of the things that we were excited about with jumping directly to an agentic AI system is the ease of maintenance and and system management. So, you know, Shree mentioned that we don’t actually script anything with our AI bot. It’s very easy to to update information on that.

For example, if if one of our branches had to close for a day or two, we could just sort of upload a quick document that said Midtown branch is closed today and tomorrow. And our bot’s gonna read the document, know that, and it’s going to not send people to that branch. And if they call and ask, you know, what branch is is closest to me, they’re they’re gonna take that out of the equation and not send them somewhere they shouldn’t, until day after tomorrow when the bot realizes, okay. That branch is now back to regular, you know, business as usual, regular business hours.

So being able to adjust on the fly with agentic AI and not have to sit and script and rewrite, you know, your menus and and your prompts and things is has really kind of been pretty amazing. It it’s been a lot easier to use AI than we anticipated. Initially, we were looking at generative AI. We got looking at AgenTic. So even though we were willing to do the generative, like, AgenTic is really just leaps and bounds better and easier to maintain for us.

Yeah. Well said.

Sri covered several things as well.

Red Rocks didn’t also didn’t have, like, an AI offering for our, you know, for our phone system.

And when we’re going down the path and got the opportunity to look at, evaluate the agent AI offering and jump in there, that was a game changer for us because it really helped provide the experience we wanted. You know, when we look back at first generation chatbots, I think the to me, the real difference is, you know, they can help with skipping touch tone menus, press one, press two, but I don’t think they significantly speed up the experience.

They don’t get me where I wanna be, who I need to talk to, or get my answers to me very quickly. A lot of them, you know, have slower speech and misunderstanding. So, you know, it’s a maturity of technology. But where when we get to Agendaq AI, I I think the differentiator, and Sri mentioned this, is it actually delivers outcomes.

So instead of, getting me to somebody, right, where I can get information or a prerecorded prompt, I can ask information. It’ll get it from the website, any docs we upload. And and if I need to talk to somebody, it’s really efficient in getting me to the right person. So it’s it’s really moving from a navigation to a self-service tool, and that is really where I see, you know, the a lot of the value.

That’s great. And it’s great you were both able to jump right into this kind of higher level system, right, not having to go through some of the pain maybe of the other ones. And I like the thing you said, Josh, where it understands language. Because with my northern accent, if I say car loan on a call line, it never knows what I’m trying to talk about. So I would appreciate your systems.

Alright. So next question, and, Crystal, we’ll start with you on this one. How does AgenTik dot ai materially improve a credit union’s efficiency ratio? I’m sure that’s something all of our listeners are interested in. And where does the fine financial impact show up first? So what was your experience there?

So that’s actually a little bit of a tough question for us primarily because we were replacing old technology and old systems. So we were replacing on prem systems with perpetual licensing, nothing subscription based. So there wasn’t a lot of of OpEx associated with what we were doing from a a cost standpoint. So when we migrated or when we jumped to AgenTic, you know, we were able to avoid large CapEx expenses and shift those over to OpEx, but it wasn’t really an apples to apples comparison. I would say that from an efficiency standpoint, we’ve had a lot of probably, more like cost avoidance. We’ve been able to maintain service levels without adding staff. We’re repurposing staff to do other things.

You know, if we’re looking at our February data I I pulled our February data just before this. Right now, we are automating in some some way upwards of seventy percent of our calls. So seventy percent, seventy plus percent of our calls have the bot answering at least a question for the callers. Some of those still end up being transferred.

And so we still are maintaining a contact center for for now. Well, we we will probably ultimately never get away from a contact center, but those people are gonna do different things. They’re not gonna have to answer what’s my balance, you know, as as people get more and more used to that.

One of the things that we we found, however, based on where we were coming from, is that our old phone system had zero integration with our old telephone banking system. So when we sit with our staff and we say we’re automating seventy percent of our calls, our contact center folks sometimes kinda dispute that a little bit and say, well, I haven’t seen seventy percent of my calls go away. But if, you know, if we truly pull the data, we are automating over seventy percent of calls, and that’s I mean, that to me, that’s impressive. You know?

We’re we’re using the same amount of people in our contact center to do so much more because they do have some free time. I think we would, we would love what our efficiency ratio would look like if we could get seventy percent of our MCC calls fully automated, and we’re working towards that. We think we’ll get there. It’s just gonna take a little bit more time.

But one of the places you know, I mentioned call cost offsets. Probably one of the places that was easiest to see a financial impact show up is that Joy, who is our bot, Joy answers calls every time the phone rings twenty four seven. So we don’t have to use a third party after hours contact center anymore.

You know, Joy’s gonna answer those calls. If she can’t help the member, you know, we we have some solutions in place for that. You’re not gonna get a live person necessarily. But if you’ve worked with a third party contact center, you know they’re really not helping your members either. They’re very limited in what they can do. It’s sort of like scripting an old style AI system. So getting away from that and not having those costs, had a a pretty big financial impact right off the bat.

Yeah. That’s huge. And getting to those higher impact, like, activities for your staff, I’m sure, is a tremendous benefit because that’s that’s where you want everybody spending their time.

Josh, what about you?

Yeah. I you know, we have a lot of the same goals, I think, around the solution.

Simply to me, efficiency ratio is how much it costs to serve a member, right, and how much we have to put into our systems, our people. And the more we can scale through automation, you know, we can deflect calls from the call center.

We can leave, you know, shorten queue times and make sure that the calls that are coming through are those high touch relationship building calls.

Because when it comes down to it, that’s our core competency is member service and making a connection with our members and and and, you know, finding solutions for them. And when they need that direct, you know, work, that counseling, that advisement, shorter call queues means our agents are taking our call center’s taking less calls, and they can focus more on the members. So when our our bot’s named Roxy. So if I use that but, you know, when Roxy is answering our phone and texting the member information that’s available on our website, you know, that they’re calling in for, you know, it’s it’s completing that need.

So, you know, we read through those, and that’s a lot of our automation is the knowledge base, you know, asking how to do something. And if it’s not something she can do directly, you know, she texts them a link to our website or, you know, the information. And, you know, it’s it seems to it seems to really meet the need. And, again, the idea is, you know, that we can scale as we grow and really not have to add as many staff.

So that’s, to me, is impacting efficiency.

Yeah. That’s wonderful. And that’s where you wanna be is meeting the members where they are with those easy needs, you know, from the agentic side and then really the handholding is what that value that we bring to the members. That’s great. Sri, anything on your side on on this one?

Yeah. I’m I’m a big believer in people helping people. I think that’s what, is the the the the industry stands for.

But I think it’s also misunderstood quite a bit. You know, people helping people, for me, means, you know, not helping your members with balance inquiries or helping them do a hundred dollar transfer.

If people are helping people, for me, means helping them to get out of the, you know, credit card debt or helping them have a better cash flow, helping them buy a home. Right? Like, there’s a lot more high impact conversations that we miss out on if our staff are too busy answering, you know, transactional calls. Right?

So, that’s where AI adds a lot of value. The efficiency ratio doesn’t mean, oh, we need to cut staff. We were talking about what if this those, AI can automate fifty percent of calls and those staff could focus on more high impact conversation? Right?

You know, let’s say, you know, a billion dollar financial institution, usually about sixty, seventy thousand members, right, for a billion dollar.

And usually, they receive about twenty thousand calls. Right? To handle twenty thousand calls, you need a twenty five to thirty member team or roughly around twenty, twenty five member team per month. For a twenty thousand calls per month, you need a twenty, twenty five member team in contact center to manage that.

So let’s say, in that math, if you’re able to, free up with AI answering half of their calls, which is very much possible, which is out of twenty thousand calls, you’re able to have AI take up ten thousand calls, then your twenty when then your staff of twenty five agent, team has so much more time to spend more time with the members with another ten thousand calls. Right? So and that goes a long way. Now imagine if because they have time, they’re consultative and really trying to understand and solve a bigger problem for the member.

Let’s say now you take that savings of ten thousand calls and put it back into your products to offer better products to your members. So to to kind of just a quick math on twenty thousand calls, you automate ten thousand of them, you’re saving enough to reduce twenty five basis points on a five hundred million dollar book of business loan.

Right? That’s the saving it funds. You know, automating ten thousand calls, funds twenty five basis point lower for a book of book of loan of five hundred million dollars. Right?

So, you you know and and now you freed up the time of your staff. You offered a better product offering to your members, and the magic will happen. Right? So you’ll enable growth automatically.

So that’s it comes down to that math for me. Right? So how do you free up time to have real conversations? And then how do you make sure that savings goes back to making products better so more and more members can afford you and and things like that?

Yeah.

So Roxy and Joy are really impacting every area of the businesses here and the member experience. So, yeah, it’s a a win win win, certainly.

Josh, we’ll start with you on this one. What operational shifts are required to successfully implement agentic AI from systems integration to staffing and governance?

Oh, yeah. It’s a lot. You know, when you’re implementing, a new technology and this was Red Rock’s first member facing AI technology, a lot of questions come up. We wanted to make sure, first of all, that we understood the risk of the technology, the capabilities of the technology, and, that we could manage that.

And partnering with Interface, we were able to kind of walk through those risks internally. You know, we expanded our, control set, so you know, to help take on AI. So when you’re talking vendor management, you know, you have new questions to ask. Right?

Where data is and and what’s being used and what what third parties your vendor uses, things like that that, you know, we may not have fully asked before with other solutions. So it’s really getting an understanding of that, mapping integrations, and understanding where the checkpoints are.

Because what you wanna do is set up guardrails. Right? So we work to refine our permissions to make sure that, Roxy was only able to do what we, you know, wanted her to do, like, on our core, right, for, you know, online banking transfers and things like that. And and we did lots of testing. We had a whole team go through testing, worked with Interface on that, really stress test that, and tested those guardrails to make sure we are comfortable and we could see, you know, how Roxy was gonna respond to certain requests.

I think the other thing that was super helpful and really important around this is having a fully auditable experience. And so we’re able to do that. You know, we can go through our retail team goes through and manages, you know, the member experience in going through the call logs, of Roxy, and we follow-up where we need to.

They look for misunderstanding.

You know, they make sure that calls are being routed to the correct, team because, you know, payoffs may go to one area of the credit union and, you know, loan like, may get another, you know, piece of loan. So we wanna make sure that we’re being efficient with where she’s being transferred. So there was just a lot of mapping testing. But as far as the system integration and, you know, things like that and the knowledge management, it was really easy.

It was really easy in the in the implementation. She, you know, she just learned it. And, you know, we tested it and made sure it was what we wanted. So I think the other you know, just the last thing when you’re talking about staff is, making sure that they’re adopting the technology communicate.

Why are we implementing this? What’s it gonna do for the credit union? What’s it gonna do for the member? And and what’s your role, right, in in in this?

Because if, Roxy is, you know, transferring members to them, they need to understand the experience, and and, you know, they need to be able to point out opportunities for improvement. So we have a team that’s focused on that, and we work with Interface to just continuously improve, the experience based on what we see. And, yeah, they’ve been Interface has been a great partner in, you know, helping us refine that experience.

Yeah. That makes such a big difference. I know in my experience with core conversions, that partner relationship and that, like you’re saying, working together with Interface AI, man, that makes all the difference of, you know, having that you’re both on the same lane and you have that support because it can be just a nightmare if if things are going in different directions.

Yeah. There is a lot of contextual prompts and stuff that, you know, we work through that we we wouldn’t have thought of.

Right.

Right? That needed to be defined. So, yeah, it it’s been a great experience, though.

Great. Crystal, anything to add there from your side?

Yeah. I will second what Josh said about Interface being a great partner. They’re so responsive, and were very helpful, you know, in in the implementation. I mean, AgenTik AI is is new, really in this entire space. Right? So, we somehow, looked up and got to be first to market for AIPV, AgenTik AI. So one of our main concerns was governance.

Our risk and compliance department and our legal team were firmly in the mix of the project just making sure that we were were checking all the boxes and fully understood what we were getting ourselves into and that we were comfortable with any risk we were taking.

You know, we created new policies. We did additional risk assessments, added to our vendor due diligence similar to what what Josh was saying. For us, though, one of the things that made the implementation a little bit more successful is we were on a deadline to replace the system, so we didn’t try to jump in all it, you know, with with every vendor integration that we want. We were able to sort of just replace our our tell our old phone banking system and and telephone, system both and just kind of get our our arms around what the bot could do as a replacement for that, and then we kind of grew from there and are growing from there.

So, because we were so concerned with the governance, we went with what I would say is probably sort of a simple implementation. That is not to discount anything that the bot does. The simple implementation has gained us a lot of functionality, but we didn’t try to muddy the waters with adding, you know, six vendor integrations in at the very beginning. So we focused on on the governance piece and controlling the risk and just making sure we were we were comfortable with the foundation we were building, and then we’re we’re moving on up from there.

Great. Yeah. It’s kinda nice to be able to kinda harness that first thing you need without, to your point, overwhelming everybody and everything. So, Shree, what about you on this one? Anything you’ve seen or experienced on this side?

Yeah. Very much aligned to Josh and Crystal and some really great insights there. I I think the most important part of it like, we all implemented, you know, non AI systems. They’re a lot more deterministic.

They’re they’re not learning software. You know, we’re we’re all, as an industry, for the first time, implementing a learning software, and that software has become very powerful every day.

So I think the fundamental minds mindset that needs to shift is exactly what Crystal is talking about, which is you don’t want everything on day one. Because a learning software, you focus on where is a high impact, high value, you know, use cases and focus on that and, you know, get more get quick value. And then the the good thing about such an AI system is it it will tell you where to invest your time next. Right?

Sometimes we get worried about trying to clean up the data.

You know? Hey. I wanna have more insights. What could be the ROI? This is also important for the executives and the board to understand.

Right? Like, to make sure these teams are empowered for a a iterative approach. Not like, hey. You know, if if you’re an executive, you you know, you gotta make a ROI case to your board to get a project approved.

Know, then you go on this long winding path of figuring out data, cleaning up data because you gotta put together this, predictable return on investment. Right? So but it’s hard to achieve clean up that data. Right? You you’re gonna like, it’s like boiling an ocean. Right? So it’s a never ending project.

So, instead, you already have some idea and what kind of calls you’re getting or chats you’re getting. Getting started with those, like a crawl, walk, and run, like, taking iterative approach makes a lot of sense because the moment you let the AI take all of your calls or chats, it is now not only able to automate wherever it can, but it’ll also start telling you what it couldn’t automate. So it gives you that clear data so you know where to invest next. Right?

So that’s a mindset shift that needs to happen. And the second part I would add to that is, it’s also about, you know, educating your staff that, this agent AI is not after your jobs. Right? Like, you know, that is so important to find that alignment.

Right? So to kind of have a clear communication and a plan. Hey. If you’re gonna if we’re gonna bring this tool, it’s gonna make the job easy, but here is a training and a picture like, here’s a path for your career.

Right? Like, here is what we want you to do. We want you to spend more time with the members. Because right now, contact center, we’re all measuring based on how much time you spend with the members.

Right? Like, oh, someone had a fifteen minutes, you know, conversation. That may not be great. Like, you know, are you taking too long to, support the member?

Right? So but those will be the norm. We want you to talk fifteen, twenty minutes. So you’re addressing an important problem for your members.

So you need to change how you measure their success and train them to take a new path of having those high impact conversation. Right? So that alignment is really important because one of the credit unions I still remember, door credit union, one of our customers. The first thing they said after going live, the staff were complaining.

The long calls have gotten longer now because all the easy calls have gone away. Right? So, you know yeah. So training your staff, give showing them a path, making sure they’re measured in a different ways while you’re taking an iterative approach.

Those are kind of key takeaways how you operationally have to change.

Yeah. It’s great. And that ties to what Josh said earlier about that bringing the the staff in and the why and what does this mean and what does it look like. It’s great how it all ties together for sure.

So, Crystal, we’re gonna start with you on this one.

How can agentic AI improve efficiency while strengthening and not weakening member relationships? And I know we’ve touched on some of this, but just your insights there.

Yeah. So, I mean, agentic AI AI is all about efficiency and improving efficiency. So, I would say that probably, you know, listen to your members. Your member feedback is is key. You need member adoption, but equally as important is is get your employees buy in.

Like Shree mentioned on the previous previous question, make sure people know that the AI is not out to replace them. It really is out to free up time so they can focus on the things that they need to focus on, increasing member satisfaction, growing deposits, growing, you know, shares per member, helping solve real problems instead of just telling someone what their balance is.

But, also, listen, you know, listen to your members. So we, Linda, you joked earlier that you’re in the north. We are headquartered in South Mississippi. I look at the Gulf of Mexico.

And so getting people to buy in for Agentic AI and and getting the AI really to be able to understand some of our our people and not not frustrate them has has been interesting. Our contact center agents actually will pretty regularly bring Joy into the conversation with members. If if they get a member who seems to have been frustrated by an experience on AI, they’ll conference the bot in, and they’ll walk through that experience together and see what happens and and show the members what Joy can do and how she can help them. And, you know, they have the transcripts of the previous call so they can tell maybe if they can easily tell, like, what happened, they can sort of explain, oh, well, you know, she understood you to be looking for this, and so that’s the answer she provided.

And we do a lot of follow-up with the interface team too, providing feedback and saying, like, our members expected this experience. The bot gave that experience, and they they do some some fine tuning on that for us. But, really, it’s it’s just you know, as as Joy is able to start doing more things for the member and as the members become more confident and, used to Joy, the only thing that AI can really do is strengthen that relationship. It’s it’s so fluid.

It’s it’s really fun to watch.

That’s great that you bring them right in like that or bring the joy right in with that. What a great way to approach it, and then it becomes a collaborative learning experience with the members and ties right back to how how we do what we do every day with the members. So that’s fantastic. I love that.

Josh, what about you?

Yeah. I I I agree. I agree with a lot of that.

You know, to me, when we introduced Roxy, we were introducing more tools to our members. I mentioned earlier, right, that I I look at AI as a self-service tool. And voice banking was you know, had a limited interface compared compared to computers. Right? We’ve had online banking adoption for years, because we can put all these features available at the member’s fingertips. Right? It just hit the click of the mouse or, you know, on their smartphone.

I think that agentic AI really expands the capabilities for voice. Right? We can tie in more services without recording answers to, you know, like, ten thousand questions. Right? And that’s where that’s where it really moves from, you know, into being a self-service tool. We didn’t have twenty four hour access to, you know, our staff before, or really phone banking, to be honest. So this has really, you know, extended our service hours.

And, you know, as I mentioned, you know, our we have a cross functional team that manages the product. So we make sure that it’s the experience we want, and, you know, we look for ways to improve it continuously. So I I think that when you put that much intentionality into something and you’re, giving the member new, new services, new tools to use, that that is a relationship strengthening, effort.

Yeah. It’s like anything. It’s how you use it and deploy it more than anything. So it sounds like you two are both having great success with it.

Corey, I’m sure you have some insight. Oh, I’m sorry, Josh. Go ahead.

I was just gonna say, you know, like, Crystal, you know, we we we talked to our staff about our our strategy for AI, which is people centric. Right? The AI is a tool to help, them and, like, our staff or our culture, they’re really our products, you know, our our service. So, the call center early on, I think, saw benefit in removing repetitive basic calls. So there’s really just wins all around, I think.

Yeah. Yeah. And I know from my life with employee engagement in my former credit unions, it it ties to all that too. Right?

Because then people feel like they’re really doing that impactful work and making a difference and not like, you’ve all alluded to, you know, spending the day giving people balances. Not that it’s not important. They need it. But Yeah.

When you can have those deeper impacts, it really does tie to that engagement side, and it makes people you know, as it rolls out more excited and they see the growth for themselves and the member impact, it’s it’s a win win all around. So, Sri, what about you on this one?

Yeah. I I think there’s a huge difference in member experience. Lot of our customers, as Josh and Chris are saying, they didn’t start this project just to improve efficiency. The the number one goal has always been how to improve member experience.

Right? Because there’s so much competition in the market now. Like, you know, if you look at big banks, fintechs, they’re offering twenty four seven support. Right?

Like, you know, but many many of us across the nation, financial institution, like Credit Union’s Community Banks, we don’t have any support after, you know, the working hours. Right? So, you know, that alone makes a huge difference in having AI supporting your members after hours because your your members have work to do. Right?

Like, they’re they’re nine to five job, and I hate when I have to take a break from work to do something with my bank. Right? Like, that’s just a huge deal breaker.

So I I I think, you know, just that alone, AI offering you after our service itself strengthen the relationship. Right? So and, you know, often, the other options we have had is, you know, we outsource the calls, and we all know the truth about that. Right? Like, you know, we are extremely paranoid to give access to all the systems.

So because of that, they can do small number of things, which means and they’re also expensive and ineffective. They they often, they send the call back to a credit union. So, hey. Like, they can’t resolve much.

So, you know, that that experience is terrible for a member. Right? Like, you know, they call after hours or during overflow, and they couldn’t get their basic questions answered. And then they have to wait for someone from Credit Union to call them back.

Like, that’s just they spend time and you spend money, and everyone is frustrated in the process. Right? So, even just AI taking overflow after hours itself is, in a big way, strengthened the strengthened the relationship. Right?

So and this AI is getting faster and better. For example, you know, Navigator is testing out a feature of ours where the AI can do upsell, cross sell, and drive drive more growth for the creatinine. Right? So now if that happens, then you’re gonna further strengthen the relationship because the AI is able to lead them towards a new product and things like that too.

So, yeah, there’s just so many benefits of that.

Yeah. Anytime you can remove frustrations, it’s a positive thing Yeah. For all sides. Yes. Yes. Crystal, we’re gonna start with you on this one. So looking twelve to twenty four months ahead, how long AgenTik dot ai evolve from a reactive service to a proactive financial engagement, which I know, again, we’ve touched on it, on the outskirts.

Yeah. We we’ve touched on it a little bit, but I’m I’m actually really excited to see what happens with our AI as we sort of start prioritizing vendor relationships that will integrate and strengthen the relationship with AI and enhance the member experience. So I think, like, originating ACH transfers from another FI or making a deposit, you know, into your into your Navigator account, paying your loan from a a bank that you have at Navigator, just decreasing that friction, letting you do those things after hours, you know, potentially decreasing friction in in the onboard experience for new members.

We’re looking at, as Shree mentioned, the the cross sell, upsell piece. So, we’re not exactly there yet, but we’re, you know, we’re brainstorming here. Like, what can Joy do for us? Where can she maybe nudge some members and and help onboard them to services that fit what they need?

I mean, you know, the bot has access to transaction history. So does that member make an over the counter check deposit on the fifteenth and thirtieth of every month, you know, at the end of the day? Well, can Joy offer him direct deposit and then talk to them about our early pay. You know, you’ll actually get your paycheck a little bit earlier if you sign up for direct deposit, and just kind of enhance that relationship and then strengthen that with the member.

We do a lot of loan prequalifications, as I’m sure everybody does. So if the bot can let the member know that, hey. You’re approved for this. And if they would like to take advantage of it, you know, she may be able to text them a link with the paperwork that they can sign.

So they never come in. They never actually even have to talk to one of our agents if they don’t want to, and they can fund that loan. And she can do all of this right at ten ten AM on a Wednesday, or she can do it at ten PM on a Sunday. And and so I really think that over the next twelve to twenty four months, we will be much more proactive because of AgenTic AI.

Great. Josh, what about you?

Yeah.

Wow. It’s, it’s hard to talk twenty four months out on AI. If you look twenty four months in the past, we’re in such a different world. But, you know, as we do that, I I think some things certainly stand out. Right? And I think deeper integrations with you know, from an internal standpoint, deeper integrations with with our other systems, our other vendors, the ability to do more more and more complex workflows, you know, being able to, yeah, deliver documents for signing and deliver them to the right place internally and archive them for us. You know, these are all things that, you know, I think, you know, systems being integrated together and building out workflows in the future will help with.

I think the other big factor, right, and this is where we really wanna make sure we protect is data. Ai can consume and analyze data, almost instantly, large sets of complex data. And the more it can analyze our members’ behaviors, the more we can offer personalized service. So if I, you know, call in every week and I, you know, check if my paycheck has been deposited and then I move money into my savings, And then, you know, maybe I pay my auto loan with the credit union or, you know, or externally.

You know, I I think in the future, these patterns will be recognized. And, you know, if I call in, it would be great. Right? Roxy just is like, oh, hey, Josh.

You know, quick authentication and, you know, hey. You got paid today. Do you, you know, do you wanna move money and pay your auto loan? So I think that the more we can use data around the experience to improve the experience, again, it it’s more efficient.

It’s more personal, and we can make that more on brand as well.

Fantastic. And you’re right. Everything’s moving so fast. I guess that is, say, two years from now. That’s great insight. Sri, what about on your side?

Yeah. And I agree with Josh saying twelve to twenty four months is too long out. You know?

Just beginning of February, there’s a AI that came out that can write really enterprise grade software, ninety percent of it, which should, in twelve to eighteen hours, which should take a staff of six people for six months in the past. Right? So it’s it’s getting really powerful.

Like, and now AI is writing itself.

You know? The next AI is gonna be much better because it’s written by itself. Right? So we are, like, going to the exponential curve now. Right? So it’s gonna be pretty different world, honestly.

I I I think I wanted to start off kinda saying one of the core mission of the credit union industry is to serve, to achieve financial well-being of our members. That’s really, like, the core of our mission.

But, like, you know, there’s seventeen percent of US consumers are financially literate. Right? So, so it’s a big responsibility. Right?

Like and because many consumers don’t know what they want, how they can solve the problem. The financial literacy is pretty low. Right? So AI, being proactive, will solve that problem, right, which it can, it can understand their financial position either through, the data from the bureau, data from the credit union, or the multiple financial institution they bank with to really be proactive and tell them, hey.

You are paying a lot on your credit card debt. If you get this preapproved personal loan offer, you will actually can pay it off and save three hundred dollars every single month that you’re paying towards the interest and put that to get a new car. Right? It’s it’s not gonna be offer.

Oh, here is this personal loan preapproved, but they don’t know what to do with it. It has to be extremely prescriptive, right, because of the financial literacy. That’s where AI is going to bridge their gap. Right?

It is where our members are in terms of understanding financial products. It is our technology is today. Right? Like, it’s because there’s a big gap.

Right? So, you know, AI is gonna bridge their gap in a significant way. It could be proactive, proactively managing their finances and helping them towards achieving goals, as well as proactively managing the fraud.

Right? So it has ability to look at all your transaction patterns. And if you if it’s for some reason, if there is a wire transfer out from your, you know, online banking or there’s a check being deposited, And it looks at your transaction and say, hey. You never send this much money to this person.

What’s going on? Right? So it can put put a block. So that’s a fraud is a big concern in the industry.

You know, I I talked recently to Josh about it and things like that, and the overall industry is a big concern. So it will be proactive at every level. Proactive in driving member goals as well as proactive in detecting fraud. Proactive even helping credit unions to understand, like, what do they need to do to drive business forward as well.

Right? So, it’s it’s it’s gonna be extremely comprehensive. You know, I do wonder sometime if it becomes proactive all the time, you know, you know, it’s it’s kind of doing some part of our job. Right?

Like, freeing us up, spend time on the things that matter. Right? So that that’s, helpful, for all of us. Yeah.

So it’s exciting times ahead.

Yeah. Definitely a lot to come, I am sure. And we have got about five minutes left, and we are at good timing because we’re on our last question for you for the group. So, Josh, we’ll start with you on this one and then roll to Crystal and Shree to wrap us up. For credit unions still hesitant about AI and member services, Crystal alluded to earlier, what is the biggest misconception they need to overcome from what you all have seen?

I I think it’s the same that we see outside of the industry with AI as a threat to jobs, a threat, you know, to replace. And, again, I I think you need to decide as a credit union why you’re implementing AI and and what your goals are and communicate that clearly.

You know, again, for us, AI is a tool that will help us scale. It will help us provide better service to our members, you know, interface AI and, you know, the pieces we have are are one are one piece of, you know, of of our AI strategy. And, you know, there’s there’s other areas that we’re looking for opportunity as well outside of just member service. We’re gonna see it embedded in, you know, so many of our vendor applications and our processes.

So, you know, developing some maturity, some experience, managing AI, I believe, is important. But, you know, I I think you need to first to overcome hesitancy. I think the answer to that is education. So, you know, webinars like this, talking with, you know, people in the industry like Sri who have, you know, strong vision.

They can help you see the benefit, and you can decide from a risk perspective what’s appropriate from your for your credit union and where to dip your toe in.

Fantastic. Crystal, anything to add to that?

Yeah. I think Josh answered that really, really well. I would say that, the the biggest miss misconception is is probably just perceived friction and thinking you won’t be able to overcome that. With education and and member handholding and employee handholding and and kind of working together, you can get past that friction. You can get through the governance piece, and really come out on the other side with a a better product for your members.

Wonderful. Sri, we still have a couple minutes left.

Do you have anything to add on that?

Yeah.

No. Happy to. I think for me, I I I talked to hundreds of financial institutions.

Right? Like, I’m very fortunate to be in that position to hear from a lot of leaders.

I think number one thing I would say is there is a a belief in the industry that agent AI is not ready for banking. Right? Like so they’re oh, it it could hallucinate or it could make things up. Or I I I think that fear is created by someone probably doesn’t know agentic AI.

Right? Like so or not building agentic AI very well. I I think that’s probably the biggest misconception I’ve heard. Right?

So which is that AI is not ready for prime time for banking. Like, you know, today, great example is Josh telling they thoroughly tested and, you know, stress tested their guardrails. Like, you know, it can, that’s a perfect example, and and a insight that this is ready for prime time. Alright?

So that’s number one. Number two is, you know, misunderstanding about, like, the kind of partner you choose. Right? Like, you know, AI everyone’s gonna do AI, But are you picking an AI partner or a AI feature?

That’s, like, a big difference between that. Right?

You you know, you you want to pick a right partner who because AI is a huge opportunity, that it can transform the industry in many ways. It’s not about a feature. It’s about right partnership and right road map that someone can drive you towards a AI native credit union. Right?

That’s a a talk I gave at GAC. It was, you know, it was one of the most attended sessions at GAC, kind of talking about what does AI native credit union means. Right? So, it it’s about it’s that how big it is.

So if CEOs and board is not involved in this discussion, you may end up always picking someone who offers a feature. But you want what you need in AI is, like, a a a top down, like, leadership involved in making these decisions, which is kind of the second point. Like, so my takeaway there is make sure the CEOs and board is involved in being the right vendor because it’s a a transformative technology and not a one feature. Right?

So, or a couple of features. Yeah.

That’s great. And I yes. I saw the on the post on LinkedIn about your reception at GAC. That was certainly one of the highlights of the event. That is for sure.

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