Arming Front-Line Bankers with AI Tools That Win Clients

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Jim Marous (00:11):

Hi, Jim Marous from Banking Transformed, coming to you from Charlotte, North Carolina at the nSight event sponsored by nCino. And what we've been really focusing on at this event is talking about the dual workforce and talking about how AI and humans are going to work together towards a better solution. And we have Will Jung from nCino and Jill Boyle from WaFd.

Jim Marous (00:34):

And so, we're going to start off with both of you talking a little bit about the research that's been done by nCino on the dual workforce. And by the way, access to the study, the research is down below in the episode notes.

Jim Marous (00:45):

So, Will, we've been talking quite a bit over the last couple of days about that research study, and talk about the realities of what's really happening in the marketplace. One of the findings was that about 90 something percent, 9 out of 10 bankers are implementing AI to some degree in their institution. How much of that are you seeing from nCino's perspective, are they really working side by side versus just implementing projects?

Will Jung (01:12):

Yeah, it's a good question. I think it depends on the bank and the institution and the risk appetite. And I think also on the study, they had about 55% were looking at retraining their people. And I think that's an important aspect because if we see the dual workforce and implementing AI, everyone's focused on adoption.

Will Jung (01:30):

But everyone's focused on adoption in the sense of you've got your current roles and how you're going to adopt AI rather than thinking, well, we've got this new technology that can do so much more now, how do we change the roles? How do we actually focus, go back to first principles or banking years, and what those roles are and really change that process, and organizational structure.

Jim Marous (01:48):

So, we're talking about an AI native foundation. What does that mean to you?

Will Jung (01:54):

It's an interesting question because I think everyone's chasing AI native at the moment. It's a bit of a buzzword. It's a bit of a cliché, and-

Jim Marous (02:03):

Took over digital transformation, didn't it?

Will Jung (02:05):

Yeah, exactly. Because we used to be digital native, now, we're AI native. And I think for me, it's more about, again, what does the technology unlock from a banking outcome perspective? And previously, I was a banker as well and worked in banking for a long time. It's that personalization, it's that promise of banking of, hey, how do we actually understand our customers and meet them in the moment when they need the banks to be that trusted guidance and advisor, and provide the banking products and services that they need.

Will Jung (02:33):

And I think that to me is what an AI native transformation is, an AI native company is. It's really understanding customers even more intimately because now you don't have, I guess, the legacy baggage that you might have had before to be able to actually complete that promise, if you will.

Jim Marous (02:46):

So, from a financial institution’s perspective, how would you define an AI native foundation and how is it really living within WaFd right now?

Jill Boyle (02:55):

Yeah, similar, right, similar to what Will just stated, I think it's really important that we even step back a little further because this AI has to have a foundation of data, it has to have good information-

Jim Marous (03:07):

Good data.

Jill Boyle (03:07):

Yeah, and it has to have that insight that allows us to really curate that experience. Once you add AI on top of that, then you're able to scale and create efficiencies and grow and take your experience to the next level. But it starts even before we layer AI on top, and it starts with a really solid foundation that is where we all need to kind of focus on first.

Jim Marous (03:32):

So, how big is WaFd?

Jill Boyle (03:34):

We're almost $30 billion in assets.

Jim Marous] (3:35 - 3:52)

So, you're a mid-sized financial institution, lower end of the mid-side, depends on how we evaluate that. How long has your organization really been doubling down on AI as a tool, but more than just a tool, as part of your entire foundation of what you're doing as a financial institution?

Jill Boyle (03:52):

Yeah, I think part of our strategy really helped us. About three to five years ago, we went, how do we do this better? You can't keep throwing people and salaries and FTE expense on top of growth and expect it to take us where we want it to go. It wasn't efficient.

Jill Boyle (04:09):

I also am a huge proponent. I think we really focused on how do we level up people. Why are we having people come in and put the same number in the same field year over year and quarter over quarter? So, it became about how do we optimize our people's experience?

Jill Boyle (04:24):

And our strategy started probably three to five years ago, where we really started looking at how do we get to a point of clean data so that we can optimize our colleague experience, and then we really started focusing on AI probably two years ago to figure out how do we take it to the next level.

Jim Marous (04:41):

So, you actually were doing two major initiatives at once. One was the data work that you had to do even if you weren't going to an AI world, you had to do it for the old world as well. But doing that at the same time, you're saying, we got to do more. But I think one thing that I take out of that is you really built your North Star around what you wanted to be when you grew up in the new world.

Jim Marous (05:03):

I mean, you were a big organization to begin with, and have a long legacy, but the reality was you're saying, where do we want to go and how do we get there with the tools that are going to be and are available at that time?

Jim Marous (05:14):

You're in the commercial space, but you can't just do it in the commercial space, you have to do it throughout the whole organization. How important was the leadership element of deploying what you're doing AI-wise? And double down on that question a little bit around, what do you have to do to make it so the employees didn't feel scared?

Jim Marous (05:31):

Because you're going back two to three years, AI was still very new, but people were already saying, it's going to take my job, now it's even more so. How do you take care of that in a true financial institution to make it work?

Jill Boyle (05:43):

Sure. I think there's two levels to that. One is leadership engagement. Our CEO is so energized by the possibilities and so excited about where we can go from here, and to Will's earlier point, how do we take a legacy infrastructure of financial institutions in the same roles and the same structure, it's been around for a long time, and what does that look like in the future?

Jill Boyle (06:07):

And I think that leadership energy and that leadership focus and intensity is really important. And then I think that feeds down into the people journey. It's not about replacing people, at least not for us, it's not about replacing people. It's about doing more with less, allowing people to scale, and valuing our people because they're so smart.

Jill Boyle (06:32):

And by allowing the technology to do those repetitive administrative tasks, our people get to really use their brains and do the analytical tasks. And so, it really was about leveling up our people and without that leadership engagement-

Jim Marous (06:47):

AI would never get a foothold.

Jill Boyle (06:48):

They weren't coming around.

Jim Marous (06:49):

So, Will, when you're working with financial institutions across the country, what do you see from the perspective of what they're trying to achieve? But there's such a gap in my research between what they say we want to do, and what we're actually implementing. What is the difference between Institution A and Institution B between moving to that real scary, actually hitting the road with it rather than just talking about it or going beyond pilots?

Will Jung (07:17):

And really what I see is probably three things that really differentiate, I think, institutions that do quite well. And those were still, I guess, in the exploring phase, as Anthony mentioned earlier today. First is, I think, strategy is always important, even more important than ever that I think, like the problems. What problem is your organization actually solving?

Will Jung (07:40):

So, if you're a bank, an institution, you're an IMB or a credit union, you have a target customer base. You're trying to sell a service or a product to maybe it is a specific segment that you're a niche in, there's a differentiator for you in that institution, in that area that you're actually providing a service for. So, what's the problem you're trying to solve, that's the first one. The context is really important.

Will Jung (08:00):

So, I always say process, the way that we organize our companies and the process that we have, it's usually the gap between the capabilities of our people and the technology of today. And so, if the technology is shifting in a very fast and rapid pace, then the process needs to shift, and you need to take your people along with you. And so, that context of how work is being done needs to change as well.

Will Jung (08:26):

And then if you think about the people, it's how do you bring the people along the journey with that context. And I think there's a retraining component as Jill mentioned, we're all hiring brilliant people. They're all educated-

Jim Marous (08:37):

And having to upskill.

Will Jung (08:38):

Exactly.

Jim Marous (08:39):

Because we have a lot of skill in the finance … you can't just say, okay, get rid of the old, get the new. You have to repair the tires instead of just replacing them.

Will Jung (08:48):

Exactly. The judgment that they've learned, the experience in the markets that they serve, the customers that they know, there are a lot of nuances. They've seen different credit cycles come across, different macroeconomic factors. There's that judgment there that we haven't documented it as an industry or have codified.

Will Jung (09:03):

So, that judgment plus the technology today, so if you understand the problem, the context and the people, those three things, if you're clear on those, they're the institutions that I think are really flourishing right now.

Jim Marous (09:16):

Well, the survey nCino did says that 89% of the organization believes there'll be a dual workforce. So, you'll have AI working besides humans. That degree of percentages is still being worked on, and certainly something that's outside depends on the part of the organization you’re working with.

Jim Marous (09:34):

How hard is it for an institution to unwind that back office? You know, digital transformation is not turning paper into PDFs, in much the same way, that you can't use all the same rules and technology and back office the way you did before. How hard is it for financial institutions to actually update their back office to be able to deploy an AI-human dual workforce?

Will Jung (10:04):

And I think it's not easy, and I think it's with people. And so, as you mentioned, you need to both the top-down vision, I think from an executive perspective, this is where we need to be. And also, that empowerment from top-down going, “Well, no, we can re-imagine.” Again, it's not about replacing the people, but your role can change, there can be more impact in your role.

Will Jung (10:25):

And so, if you have that top-down and bottom-up thinking in terms of, well, actually, how can we be better as a bank with this technology? Change the back office. Because a lot of the back-office functions, I used a previous example at some of the institutions that I worked with, they had a back-office function that was doing documentation.

Will Jung (10:42):

They were creating documentation for loans. All the people that they hired had law degrees. They were really well-educated people doing documentation. So, when first nCino gets implemented, they were scared, are our jobs going to get replaced? Because my job is documentation. I was like, no, the job that you have, the impact that you have is to make sure that we are legally compliant both from our perspective and from a client, we're protecting you as well. That's your impact.

Will Jung (11:09):

So, if you're bringing it back to first principle of what you're actually hired for and the impact they can have, I think that's the conversations the organizations need to have from both top-down and bottom-up.

Jim Marous (11:18):

Well, and that's where you bring in compliance and other areas to say, “We want you all to work on this together,” because how many years have you been in the banking industry? How long have you been going with signature cards seeing that was what was required when you really just know your customer and in a digital world, know your customer can be completely digital, take a new account opening experience down to three minutes as opposed to 14, 18, 20 minutes.

Jim Marous (11:39):

And getting away from some old legacy thought patterns, and to get a group around that says it's your job to get us to three minutes so that when you get all done with all your implementations, compliance and say, we still need a driver's license, which kind of disrupts the whole process.

Jim Marous (11:53):

So, in the real world, which we're talking about in the banking world, you're on stage today, it's obvious you're well ahead of the curve with regard to what you're implementing. It took a mindset, as you said, a culture, but it also started with data. What do you have to do in your organization to have the data ready for an AI world?

Jill Boyle (12:16):

Yeah, I think it's really important that we understand all the components, first is figuring out what all there is. There are so many various pieces and historically, financial institutions have been very siloed.

Jim Marous (12:28):

Siloed. I know that word.

Jill Boyle (12:32):

And that matters. You're going to have to bring it together to really be able to carry and understand and allow AI to effectively do what it's good at. Someday AI will be able to handle the silos itself, but for the most part, that's not there yet. And we're bankers, we want control of that.

Jill Boyle (12:51):

So, bringing it into a central repository, which was part of our five-year outlook four years ago, so that we can leverage it and create in an ecosystem of open APIs that allow us to do what we need to do with the various components was really critical to the start of the journey.

Jill Boyle (13:09):

The other thing it helped us do around the middle layer is it helped us identify what's the biggest impact. How do you prioritize all of the changes that have to happen as part of this evolution, because if you don't have a plan, and if you don't have a prioritization and you don't have a buy-in from all levels of the institution around that plan, it's going to be really hard. It's going to be really hard.

Jim Marous (13:35):

I interviewed a person from U.S. Bank once, and he said, “We brought all these people in the room and said, you have to streamline process, you have to get the data ready for implementation.” He goes, “But you got to realize also that as a decision-making organization, we can't ever get out of a meeting with less steps than we had to begin with.” So, we had to set the ground rules and what we were trying to accomplish.

Jim Marous (13:53):

And you have to, as you said, make it so everybody's on the same page, you have to remember to bring in people that you normally would not bring in because you know they're negative Nelly. And you go, “I need that because I'm not going to move forward unless I get everybody's buy-in.”

Jim Marous (14:06):

From the standpoint of also, you're not the biggest organization where you're not building everything internally. When you look at partners — interesting SpaceX that Elon Musk says, “I have to continually upgrade my partners because I'm only as fast as my slowest partner.”

Jim Marous (14:25):

So, when you're rethinking your data strategy, when you're rethinking, probably to some degree, your core strategy, when you're rethinking your AI implementation strategy, how are you selecting partners today to be able to be fast enough to keep up with what you consider to be the speed you have to move?

Jill Boyle (14:43):

Sure. I think picking partners is a really important item to talk about and evaluate. We really look at who's nimble and who is open to partner and collaborate. As soon as a vendor walks in our door and tells us how we're going to do AI, they kind of lose us. We don't want someone that tells us how to do it, where their business is tech or whatever their business is — we want a partner who's going to have open conversations with us.

Jill Boyle (15:12):

And when we have those conversations, if they're collaborative and engaged and have the same energy and excitement about where we're taking our business, we're probably taking that partnership to the next level.

Jim Marous (15:26):

Let's take a short break here and recognize the sponsor of this podcast.

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Jim Marous (15:33):

It's interesting because we have seen that five years ago, right before COVID, we were all, as a financial institution, buying what the vendors were selling. We're now the best companies because there's such a differentiation between where you're on the maturity level, digital maturity level and AI maturity level; that if you're a leader, you have to find the partners that are willing to say, “I will change our business model to a degree to help you get to where you need to be.” The best partners are loving that.

Jim Marous (16:04):

Because they don't have to build their runway, you're building it with them (not for them), and as well as a collaborative solution, and you're also learning from their other leading partners. And you don't get afraid of sharing with others because you go, “I still know my base the best,” which is a good thing.

Jim Marous (16:25):

From a commercial standpoint also, when you talk about the AI-human parallels and the tools working side by side, how are your commercial calling officers loving AI? Because it’s interesting, I haven't been in banking for 45 years, it’s been a long time, but I've been working with banking my entire career.

Jim Marous (16:46):

And I thought about how cool it would be to be a commercial calling officer, having all this data and insight that usually my clients don't have. I can bring answers to them that they aren't finding on their own to bring … I can be their hero on their behalf and make my client the hero within their organization.

Jim Marous (17:03):

Because I can share things that they haven't asked the questions right up to now, and they're not all AI proficient. So, you go, I want to find the ones that aren't up on that curve because I can bring more to the table. What do your commercial calling officers really think about that? And even your branch people from the standpoint of being able to use data and insights to actually implement agentic solutions?

Jill Boyle (17:24):

Yeah, it's interesting, we've really pivoted our model, so relationship managers can be stuck in their ways sometimes, I'm just going to put that on the table. So, it's hard.

Jim Marous (17:33):

Loan officers, basically any part of banking.

Jill Boyle (17:35):

Exactly, yeah, and it takes a minute. It takes a minute to get the energy and the excitement. And we really, a couple years ago, started this initiative to help them understand that we're taking their time back from those administrative clicks that they were doing, and the time that they were taking moving widgets from here to here.

Jill Boyle (17:55):

And we're giving them that time back to really focus on the community and the advisory aspects. And now, we've got them with an app on their phone that they can ask a question or their client-

Jim Marous (18:06):

So, you actually give them access to data, you give them access to the tools.

Jill Boyle (18:10):

Yeah. And so, we build them some experiences.

Jim Marous (18:14):

The democratization of the insight and the tools makes it so they feel comfortable because they still have some control over how they leverage those.

Jill Boyle (18:21):

Exactly, yep. And it takes a minute to get them there. But the first time they have that wow from their client, because of that data and information they showed up with, they're all in.

Jim Marous (18:32):

And see their peers doing well where they go, “I don't want to be the last on the list of sales.” So, as much as we talk about this, makes it sound like it's all mom and apple pie. The reality is you get negative situations or things that the aha moment, you go, “Oh, didn't see that coming.” What was one of yours? That you had it at WaFd where you said, “Wow, didn't see that hurdle being as much as I thought it would be?”

Jill Boyle (18:57):

I mean, honestly, it's the people component because I get excited about change and I get excited about new and forward movement.

Jim Marous (19:03):

And they go, “Oh, here comes Jill again.”

Jill Boyle (19:05):

Exactly. And the bankers that have left because they don't want to or the people that don't find it positive, that's shocking to me. And I take it very personally, and I always think I got to step back and figure out how do I bring them on the journey? But that, I take it very personally.

Jim Marous (19:23):

It's interesting because I just interviewed a person from Synovus who is in charge of the human aspect of digital transformation. They're in the middle of a merger right now, they're doing AI. They're doing all digital transformation in its rawest form, and closing their branches. They have all these things that all take communication.

Jim Marous (19:39):

But we sometimes underestimate that power. But from your perspective, you said it really well, that my enthusiasm can be a put off at times because I make it sound like everything's so easy. And in the real world, we're talking about people's lives.

Jill Boyle (19:52):

Yeah. We’re moving their cheese.

Jim Marous (19:53):

And if they have a negative thinking, if I don't get on board, I could be without a job, that's a real world change. From a positive standpoint, what did you see as being something that, surely, I didn't see that thing coming and that's pretty fun.

Jill Boyle (20:09):

I think we have the opportunity to communicate and manage change in ways we never have before. We have more abilities to get in front of people and celebrate the wins and build energy that we didn't have before.

Jill Boyle (20:23):

We're not sending out newsletters weekly, we're not sending an email with all the company updates, we can build ride-in applications, we can build messaging and information and trainings. We're able to do learning and development differently than we ever had before. And I think it's a huge win to watch how quickly we can manage that change when we focus on it.

Jim Marous (20:47):

So, Will, the nCino report came out about the whole AI human thing. What was something in that research that was like a, “Oh, wow, didn't see that coming,” either positively or negatively?

Will Jung (20:58):

I think the adoption one. So, everyone's focused on adoption, assuming there's going to be ROI on the back of that, and then I touched on it before, it's-

Jim Marous (21:08):

And adoption is about the implementation. We realize after the survey is done, how the words make a difference and you're going, we ask how many people can open an account digitally on a mobile device? Almost everybody can. And then we get down to, but is it really digital? Is it real?

Will Jung (21:22):

Exactly, exactly. Implementation, adoption piece, and just the training of the people. Not as many, I would have imagined. I would imagine a high percentage of institutions think about re-skilling. And I think that's going to be interesting.

Will Jung (21:35):

As Jill mentioned, it's exciting times because before we had people operating systems, that was their job, like I need to work for the system almost. Now, the system works for you in a way, and that's really exciting. So, you can actually go back to the core of banking, that's what the technology should be doing for you. But because the identities that they formed in careers was so much about the process, and that's been the scary part.

Will Jung (21:59):

And so, I think that for me has been interesting in the sense that, okay, there are certain institutions who maybe haven't reached that point yet, but because it's still only early days with the technology, but they're all going to reach a point where it's like, alright, there is going to be a big people aspect of this, as you mentioned, Jill, that we're really going to focus on. It can't be a side project because I think something that’s a side project-

Jim Marous (22:17):

Not a technology solution.

Will Jung (22:18):

It's not a technology shift. It is a technology shift in the sense of it's enabling it, but really, it's an organizational shift.

Jim Marous (22:24):

So, we're moving very fast right now, a bit faster than we ever have in the industry. I use the same … we never moved this fast, we never moved this slowly again, and so it's not going to all of a sudden slow down and let us catch up. But with speed comes risk. How is nCino, but also how are you seeing your clients being able to balance risk and speed?

Will Jung (22:48):

Yeah, so there's a couple of elements there. I think one is going back to, hey, do you understand the actual use case that you're solving for? Rather than going, hey, we've got AI now, let's try AI in everything. Because as banks, you need to be profitable. There's a P&L component of this. You need to understand token costs. You need to understand that not everything needs a large language model.

Will Jung (23:08):

And so, when we think of it from an nCino perspective is, institutions are trusting us to provide the best solution for the problem that they're solving for the customer. It sounds very simple but that’s how we actually-

Jim Marous (23:18):

Because in some cases, you're the human versus the AI, because they may not be hiring their own people to do that.

Will Jung (23:23):

Exactly, 100%. And so, when we talk to our product teams and engineering teams, we always go, “Make sure you're using the right tool for the right job.” And sometimes, simple code is just as good, if not better, and it's reliable, it's cheaper than a large language model. There are certain things that a large language model enables now from a data aggregation perspective, it's ambiguity, but again, put the human in the loop to manage that risk.

Will Jung (23:46):

And I think if you understand the technology more, and I think this is where the culture of innovation and experimentation is important, is really everyone needs to understand to a certain level — you don't need to know the deep, the crevices of how a large language model actually works, but you need to know at least what it does, how it's actually being used, the cost behind it, so that you can actually make from executive perspective down all the way to individual contributors, you can understand what this actually does.

Will Jung (24:11):

I think that's important, because the more you understand it, the more you experiment and really see the potential of it, but also what is it in reality, in the real world, I think that's important, because I think there is a lot of hype, as you know, out there, and this is going to, to the extent of, hey, it's going to replace everyone. Like 50% of white-collar workers, they say, “I'm going to be gone.” There's a lot of confusion, what LM can do or can't do.

Jim Marous (24:33):

We read headlines. We read bait click, and I live on bait click once in a while on the podcast, but the reality is, is it real? And we read below the headline to say, are we really letting go of this many people? Are we simply not replacing some people that have left? And that's a big difference in headlines, not nearly as sexy or as fun to read, but a lot better for employees to understand. It's not like we're all of a sudden going, “Your job's always at risk, you always have to be there.”

Jim Marous (25:00):

On the other hand, you have to think about the risk element, you can't forget about that. As I mentioned, from a risk perspective, how does your organization manage risk as opposed to avoid risk?

Jim Marous (25:10):

Because you came in the banking industry 20 years ago, I guess, two decades ago, when really we we’re hired to avoid risk. If you worked on the teller station, you had to balance to the penny every night. I mean, it got drilled into you very quickly, but AI works in a different risk environment and to move forward in digital transformation, all the things are going on, back office, front office, moving forward — how is your organization managing risk in conjunction with the speed you're having to move at?

Jill Boyle (25:37):

Yeah, I think it's interesting we now have a standing weekly meeting with our technology steering committee, and our risk partners are part of that, our CISO is part of that, our CIO is part of that, the executive team is all there.

Jill Boyle (25:48):

We really put everybody at a table every week and review a dashboard and monitor metrics to go, “Is this doing what we expected it to do or wanted it to do? What is the usage looking like? What's the adoption? Are we seeing any spikes that may tell us there's risk happening or may make us want to dig a little bit deeper?”

Jill Boyle (26:08):

We're spending a lot more time monitoring those insights and figuring out if they're actionable than if you think about it, not that many years ago, we waited for quarterly board reports and quarterly, we would look at what's happening. And so, we think we need to look at how do we do it? How do we do it differently? And then what is the data telling us? There's so much data that comes with all of this AI.

Jim Marous (26:31):

Instantly available.

Jill Boyle (26:32):

So, we've got to change our cadences, and then our actions based off of those reviews.

Jim Marous (26:40):

So, you're speaking at conferences, you're putting out there as an organization that's ahead of the curve overall. How are you staying ahead of the curve? What's on your roadmap over the next three to 12 months that you can share that maybe just categorically, what are you working on? What's your organization's mission? Not just yours, yourself, but the organization, what is it trying to solve for right now?

Jill Boyle (27:04):

Yeah, we have a couple of things in flight right now. We're working on our call center on being able to leverage AI to answer some of those basic phone calls. And I know that seems basic, but for community banks, it's a big deal. We don't want our clients sitting on the phone for 40 minutes waiting for us to tell them they're out of number-

Jim Marous (27:19):

And it doesn't mean replacing head count. It's not putting them on a three-minute time clock and going, we can now give you six minutes, we can give you 12 minutes to actually get into the minds of the customer rather than just giving their balance.

Jill Boyle (27:30):

And then when we do need to be on the phone with the client, when it does make sense, we're able to deliver a higher level of experience because we got the noise out of the way. So, that's a big focus right now. And then from a commercial banking standpoint, I'm really focused on how do we make that device they carry in their hands all the time, their single point.

Jill Boyle (27:48):

And really how do we integrate everything and how do we allow them to come out of a meeting and get in their car and talk and say, “I just met with so-and-so and we're going to have this opportunity and I need to follow up on this, and oh, by the way, her daughter's getting married this summer.” And allow the system to generate reminders and notifications and help support our bankers so they can-

Jim Marous (28:06):

Give us questions to ask.

Jill Boyle (28:07):

Yeah. So, they can grow.

Jim Marous (28:08):

It’s interesting because it really empowers the employee, which makes the employee experience better, which is where the whole conversation started. That one of the things you're focused on is making a better employee experience when we don't think about that, we think about the external.

Jim Marous (28:22):

So, not just for your organizations, but I haven't asked this of anybody in the podcasts I've done. On a personal level, how are you using AI tools on a personal level?

Jill Boyle (28:33):

Oh man! Our AI does our meal planning now, which is great. Our AI does our budgeting, our AI is helping our kids-

Jim Marous (28:39):

I'm talking about the bank, but you're talking about at home.

Jill Boyle (28:41):

No, like at home, because I think we as humans, to be leaders in an industry, we at home have to leverage it as well. And so, I've been doing education series with my teams on how do they make their lives easier?

Jill Boyle (28:57):

Because if their lives are easier, then they think about how to adopt it at work, and how to lead their teams better, and how to simplify the processes, the task rotations, the late night (we always have a late shift person) — scheduling the late shifts, scheduling around vacations. We can implement it in so many different ways to be better leaders and be more effective. But if they use it at home, they come in with great ideas to lead their teams too.

Jim Marous (29:25):

How about you personally to make you smarter? What do you ask ChatGPT or Claude or Gemini or any of these tools. What’s the most recent thing you asked just on a personal basis, just to fortify your mindset?

Jill Boyle (29:38):

Well, it's interesting. I'm doing a school program right now, and the most recent thing I asked it was what is the optimal service model for the lines of business I support?

Jim Marous (29:50):

Wow, very cool.

Jill Boyle (29:51):

Yeah, it's cool. Because what it does, it may not tell you the answer, but it makes you think differently than maybe you would have if you just did it yourself. And that’s what I like.

Jim Marous (30:00):

It prompts a new question, you go never saw that coming.

Jill Boyle (30:02):

Yes. It challenges us to think differently.

Jim Marous (30:06):

So, you're a tech guy, so how do you use AI-

Jill Boyle (30:08):

Your answer is going to be really different.

Jim Marous (30:10):

Well, maybe not because I'm asking on a personal level, what have you used AI for recently that was just something you just said, I want to know this or I want to implement this, or something along that line.

Will Jung (30:20):

So, on a personal level, it's all around learning. So, there's two aspects, one is my daughter. So, my daughter doesn't really like maths. And so, I was like, “Okay, how do we make maths fun?” So, we created an app. So, it was almost like doing product development again.

Jill Boyle (30:33):

That's awesome.

Will Jung (30:34):

So, it's like, okay, what is it about maths that you find hard? Which subject do you find hard? What do you like from games? Do you like a role-player game? Do you want turn-based games? Alright, so that's become a real thing now. So, with my son and my daughter, every time they have something that they don't really like learning, that's usually my go-to now.

Jim Marous (30:50):

And you give them access on their mobile device to that-

Jill Boyle (30:53):

On the iPads, yeah.

Jim Marous (30:53):

She can update and say, you know what, I found out I was wrong on what I thought I liked. I want to change this lesson plan. That's very interesting.

Will Jung (31:01):

Yeah, so that's been really fun. And for me personally as well, I'll have a topic. So, crypto is a recent one that I've gone back into, just around blockchains and going, well, I actually want to go deeper now. Create a lesson plan for me. So, it's another app that actually takes me through because I just don't want to read, because I don't have that attention span anymore. So, it's that app to keep me engaged and so that's how I use it a lot.

Jill Boyle (31:22):

Process information is a big one. I'll drop something in there and go, give me the keynotes, like the top points on this.

Will Jung (31:28):

Yeah, personally as well.

Jim Marous (31:29):

It's interesting, on a personal level, even though it's business, from my podcast, I do insight videos now, which I actually take a topic I want to talk about and put it, bring it to life. And sometimes the ideas come out of nowhere.

Jim Marous (31:39):

And so, real quick case study. I looked at my Oura Ring one day and I said, what could retail banking learn from my Oura Ring experience? And it nailed some of the things I would never have thought of. As opposed to giving me a rear view, mirror view, like my banking institution does, I'm not waking up every morning to find out what my banking engagement is or what I should do financially. But I am checking my sleep score. I am continually reading about how I can improve it. So, it not only tells me what the score is, but what it means.

Jim Marous (32:08):

When you think about it in the banking world, you go, that's what we really want our customer engagement to be. And then I was doing the podcast or the insight video actually in the botanical gardens in Phoenix and on my way to the filming, I said, “How can I connect what I'm doing in the desert to what I'm doing here?”

Jim Marous (32:26):

They said, much like the digital transformation, what a consumer wants to know about their path going forward, a cactus collects water during times of need or before times of need when it's the wet season, just store it for the tough season; how can we help our customers prepare for those down times financially? I'm going like, oh man, better answer than I could have come up with.

Jim Marous (32:49):

And I take the ideas and then I expound on. But it's interesting because it helps you think, it helps you think outside the box. When you learn how to work with it, you realize its tendencies to make you feel really good all the time.

[Music Playing]

Jim Marous (33:00):

Well, this was great. And I use now, if this was really a C answer, what is your A answer? You realize they've completely rethought the question and gives you other ideas you can put into it, but it's interesting.

Jim Marous (33:11):

Both of you, I love talking to financial institutions that are actually doing the things we talk about all the time. And with people from nCino who are helping institutions move beyond their comfort zone. At the end of the day, I think that's what we're talking about, is how the institutions move out of the comfort zone, use case studies, use the resources that are available.

Jim Marous (33:31):

Even if you're not a client of nCino, you can call nCino and ask a question about how would this be implemented? You can also, as you said, talk to all your partners saying, what have you done for me lately to move us forward in our vision, our North Star, to make us a better institution so we can keep that lead in the marketplace as far as our implementation of AI.

Jim Marous (33:50):

Oh, and by the way, the thing she maybe didn't share that says, oh, this is a problem I have, this is a problem I have. How can your vendors and your solution providers do better at making it so you can raise above the norm? Thank you both for being on the show. Appreciate it.

Jill Boyle (34:02):

Thank you.

Will Jung (34:02):

Thank you.

Jim Marous (34:06):

Thanks for listening to Banking Transformed, the winner of three international awards for podcast excellence. If you enjoy what we're doing, we would really enjoy a positive review. Also, check out my recent articles in The Financial Brand, the research we're doing for the Digital Banking Report.

Jim Marous (34:21):

This has been a production of Evergreen Podcasts. A special thank you to our senior producer, Leah Haslage; audio engineer, Chris Fafalios, and video producer, Will Pritts.