Innovation at the Speed of Business: Transforming Banks into Digital-First, Customer-Centric Organizations

Banks' customer relationships are becoming increasingly transactional, putting trust and loyalty in play. As a result, three-quarters of customers have a relationship with at least one other bank. With digital challengers and fintechs gaining ground, traditional banks need to strengthen their positions—fast. Learn what steps to take to engage customers through data-driven personalization that puts tailored experiences, advice, and new products into their hands.

Transcription:

Mary Ellen Egan (00:11):

Good morning everyone. Thank you for attending our session: Innovation at the Speed of Business, transforming Banks into digital, first customer-centric organizations. My esteemed panelists are Wes Hummel, Chief Product and Technology Officer at MX; Kristen Rankin, EVP, Head of Digital Regions Bank; and Jason Schlitz, AVP, Senior Product Manager, Digital Channels, Woodforest National Bank. Thank you so much for speaking with us today. We've had a lively prep call, so I'm hoping I always tell people you're the experts. I'll just be over here in the corner if you need me, but let's start with you, Kristen. So one of the things you talk about is the difference between personalization and customization.

Kristen Rankin (00:54):

I think about customization as the user or our customers defining their experience. The most simple example is account nicknames, and it becomes more important when you start thinking upmarket in the commercial space. Different users, particularly a treasury management controller, might want a different experience than account payables, for example. So it starts to become more important when you think of the market. Personalization, however, is when as the creator, we're creating those data-driven experiences. So everything from marketing to servicing experiences, it could be at the segment level or hyper-personalization at the user level. And I certainly think the retail industry is a little bit ahead of us in the financial services industry, but I'm encouraged by the conversation at the conference here in that area.

Mary Ellen Egan (01:47):

Jason, would you like to give your thoughts?

Jason Schlitz (01:51):

Good morning. Nice to meet everybody. So thinking about the larger context, innovation at the speed of business, I think that can be overwhelming for a lot of banks because they've built systems on top of systems over the years. And so I like to go back to the fundamentals when things can get overwhelming, and I think about a lesson that I learned in high school band: always focus on the fundamentals. So I think the first thing is you have to really step back and focus on the business problem that you're trying to solve. Good old-fashioned business analysis. In all the requests that we get and the problems that we hear from stakeholders, it's easy to just completely get lost in the shuffle of what is the problem that I need to solve. So go back to the fundamental questions. The second thing is, after you've done that, focus on the fundamentals and then you have to execute at some point, right?

(02:54):

So to understand what you need to do, you've got to quantify the data. We have data from so many different systems and sources over the years. Again, that can be overwhelming. So how do you do that? You go back to the old-fashioned agile principle of you have to start somewhere. You have to start small. So start somewhere, don't get overwhelmed and just continue to work through the process, and then eventually you've got to get to execution. So how do you be successful in that? It goes back to, I think, the third fundamental: collaboration. Don't feel like you can do it all by yourself. Find a partner. Find a partner like an MX or someone that can help you work through all those data challenges and solving the true business need that you need to solve.

Mary Ellen Egan (03:39):

Wes, one of the things we've talked about on our call is you emphasizing that necessity for AI, for achieving outstanding personalization results and also the importance because it's a highly regulated industry, banking then having a risk and compliance and regulations and sets. So could you talk a little bit about how you view that and how you kind of achieved that?

Wes Hummel (03:58):

Yeah, absolutely. I think the regulatory space is going to, by nature of AI, have to change. AI is coming fast and furious, and if you're not using AI daily, and if your teams aren't figuring out ways to use AI within their workflows, within their products, you're going to fall behind. And so I think the regulatory landscape is going to have to adjust very quickly to that. At MX, what we're doing with personalization as it relates to AI is really understanding what our client's consumers want, meeting them where they are, understanding even there, we're using AI to determine stages of life. So when you're moving, when you may get married, when you have kids, to be able to help our clients serve up very relevant products and services, of course, user permissioned and consented so that we can help them in their financial lives. And so I think AI is going to absolutely just like it's transforming every business. It's going to transform this space and it's going to be tough. To your point with the regulatory landscape, it's going to be very hard because by nature there's risk aversion there and it's going to be very important to be able to protect data, ensure that data is secure, but also ensure that AI can be used for the personalization of those products and services.

Mary Ellen Egan (05:28):

Kristen, how are you using AI at Regions?

Kristen Rankin (05:30):

Yeah, so we're using it in a few different ways in the digital space. So mobile banking, online banking, our public site on.com, we're using AI to drive offers, content, insights based on propensities to select. So next best message is an example. We're also using it with our associates in the small business and commercial space to deepen relationships as they're having that conversation. And we're definitely thinking omnichannel connected channel. So having the data across all the channels is what really drives the benefits of personalization. So if there's an experience that's happening, if it's driving a call, it's probably not a positive experience. So how are our associates able to support in that experience and really transition a negative experience into something positive? And I love the opportunities with AI. When you think about being able to understand sentiment on a call, probably not a great time to suggest an offer of a new product. Maybe it's an opportunity to suggest you're approaching a fee limit as an example, to provide some information that's going to help out our customers. So that's how we're thinking about it.

Jason Schlitz (06:39):

We're using it at Woodforest in a number of ways as well. I would say on the front end though, a lot of that is still on the roadmap. It's coming because we're still assessing how can we use AI to help us make better informed decisions. How do we aggregate all this data so that the data is making the right decision for us and to help our customers? I'd say on the implementation side, our use of AI is heavily in the fraud space. It's a huge focus for us right now because the bad actors that are already using AI, I heard today that something like 70% of Fortune 500 executives have now been a victim of a deepfake? If that doesn't scare you, I don't know what does. So the bad actors out there are using AI, these new technologies, and they're trying to do it faster than anybody here in this whole conference hall. So we have to constantly stay ahead of the race and use those tools to stay ahead of the bad actors out there.

Mary Ellen Egan (07:33):

So one of the things, Wes, we talked about in our call, which I thought was a provocative statement, but it's true: "Payments will occur when they need to occur, and the role of the bank is to power those experiences."

Wes Hummel (07:46):

I mean, look, I have three young daughters, and they're Gen Zers, and they call me a boomer, and I try to explain to them I'm not a boomer, and then I explain the years that a boomer is, and they say, 'okay, boomer.' But they're young enough. They want experiences to meet them where they are. They don't necessarily want to go interact with the bank. They want payments to be ambient. And if you think about the experience that Uber introduced years and years ago, where you just get in a car, you get in a car with strangers, you get in a car, and then you get out of a car and you don't pay. That's the kind of experience that the newer generations are wanting. And so as we think about the experiences that banks have to provide for their customers, they have to figure out how to be part of that ambient workflow and how to meet their customers where they are. And I think that's going to transform this landscape.

Mary Ellen Egan (08:45):

On an earlier panel that I moderated, one of the speakers had said she works for USAA Bank. She said, "Banks aren't in competition with each other, they're in competition with retail," because of how well an Amazon works or an Uber. So what do you think about that?

Kristen Rankin (09:04):

Yeah, absolutely. Our customers are having their digital experience, and that's what they're comparing us to on their apps every day, their usage. So we're certainly measuring our engagement based on our adoption rates, how frequent the sign-ins are, how engaged our clients are, how much time they're spending on our digital solutions. But that competition is real, which is I think why we're all looking at personalization, knowing the real estate of a mobile device is pretty small, so we know what content we're putting in that space. If it's a service, if it's a cross-sell opportunity, that's all part of the experience. So we definitely lean into our research team and our experience design team and spend a lot of time thinking about what Jason was talking about. Let's test out, let's identify the problem that we're trying to solve and make sure we don't have solutions that are looking for problems. So really being thoughtful about that and actively looking at third-party information and primary research as well.

Jason Schlitz (09:59):

I think it speaks to the ease of moving money. How easily can your customers move money, pay bills, send money to a friend, etc. Banks are traditionally savings institutions. Now, banks are all about ease of use and moving money. And you talk to customers, I think three things this week: AI, crypto. But a third theme that I've heard a lot this week at the conference is so many banking customers now have more than one bank account. Why? I overheard a customer in the elevator yesterday talking about this. They're not here at the conference, but they saw my badge. They said, 'Hey, my badge is over there. Are you at the banking conference?'

Kristen Rankin (10:49):

Yeah, yeah.

Jason Schlitz (10:50):

And they mentioned, 'well, we have three different banks.' And I asked them why. And they said, 'well, our local bank is really great at service, and that's where our direct deposits go. So we go to our local bank because we have our relationship with them, but we also have a digital bank because they have a really great rate on a savings account. And then we have another bank because other relatives that live in other parts of the country, like our kids, etc., they primarily bank with this other bank, and it's just easier to transfer funds within that bank versus between the banks, at least in their mind.' So how do you make the movement of money across these accounts as easy as possible for your customer? And I saw a demo yesterday that showed that very well incorporating crypto and trading into the platform.

(11:38):

And I thought that was really something to look at because that's something that we're focused on as a bank is there's all these platforms out there, see other mechanisms for P2P, Cash App, etc., our own in-house app. And we look at the performance and transactions on those different platforms, and we're constantly asking ourselves as they shift over time, you can see them shift, right? Why are they shifting? Why all of a sudden did we see a big spike in Cash App in a dip in this other money movement app? Well, they rolled out a new feature. So again, I think it speaks to how easily can your customers move money?

Wes Hummel (12:16):

Yeah, you're absolutely right. I mean, the research we've done at MX shows that an average consumer has five to seven different banking apps and financial apps, and it's because they're going for that ease of use. And you talked about Amazon, one of Amazon's obvious superpowers is just the amount of data. And so at MX, we sit in a good spot because we hold, we not only have the banks held data, but we also have aggregated data that comes in. And with our new data access products, we have the ability to look at data going out and seeing, 'oh, where is your money going to?' And so what's really important about that is once you start to get a holistic view of a consumer, you have all that data just like Amazon has. And Amazon actually pretty soon will be sending you stuff that they think you want. It just reminds me of Columbia House.

(13:08):

For those of you who remember that Columbia House used to send you all these CDs, 'well, take what you want, send back the rest.' Amazon's going to be doing that with products because they have so much data that gives them such good visibility into the types of products that you likely will like, and they make it so easy to return. And so when you think about how that applies to banking, the products and services, the reason they have those five to seven apps is because they want to make it so easy to do what they need to do, but they don't want five or seven apps. And so the institutions that figure out a way to integrate themselves into, as you said, into competing with retail and being in that space, are going to be the most successful. And that's going to require using data.

(13:51):

And what we hear from our clients is that 'we have so much data and we don't know what to do with it.' And that's where we at MX are using AI to pull all this aggregated held and data out to determine what are the best products and services that are going to help customers, and how are you going to meet them where they are and give them things that are relevant to them because when they feel like you're giving them offers that are relevant, then they're actually more likely to use it. They feel like you're just spamming them with offers or like you said, giving them offers when they're calling about something they're upset about, that's not going to go well.

Mary Ellen Egan (14:26):

Yeah, for me, so I get my bank, which I won't tell you who it is, but I get these now, buy now, like, 'oh, you want to split up this payment?' And that would've been really useful for me in my twenties when I was a waitress and always broke, but I don't ever use it. 'Why do you keep sending me this?' So sometimes it can border if they're not careful. I think it can get a little bit on creepy or annoying, and that's the last thing you want. So how do you shape know that the right time to send out the right message?

Kristen Rankin (14:58):

I think there's a balance, especially with AI and splitting it or thinking about it two different ways. One, the propensity to accept and then what we might want as a company or institution to drive are two different things. Using AI to drive what we want versus what a customer might want is very important. Certainly testing out the two options, getting a balance. I think there's a data point that I saw. I want to say it was an Accenture study where it said mid 70% of users want personalization from their bank, but only about 3% are using them. Now, I can't quantify how they interpret personalization, but we have to be really thoughtful to your point about it being relevant and timely in the moment for what the customers and not continuing to surface the same content and making sure it's appropriate for the audience. So I know we're all driving towards personalization, but getting it right is important. Otherwise we'll sort of overwhelm and create a negative sentiment.

Jason Schlitz (16:00):

Just to add, when you start talking about personalization, it's so important and yet it can be creepy, right? With AI, I mean, just to call it out for what it can seem like. I know it does to me sometimes when I get solicited or get marketed for something that was related to an incident or a relative I haven't seen in a long time, and I start getting information about that. 'Hey, do you know this person?' etc. So making the personalization feel personal. That's the challenge, I think. And empowering the customers so that when they go through the customization experience, they have the knowledge and the education to make that customized experience to them relevant. So it really feels personal, right?

Mary Ellen Egan (16:51):

Excuse me. Let's move away a bit from the consumer and talk about the workforce. So what do you think is the role of AI in data management and the workforce? What was that, the role of AI in data management and the workforce?

Kristen Rankin (17:06):

So definitely what comes to mind is marketing. And we think about our marketing teams, traditional, think about campaigns very different than maybe how our workforce is in the technology space and digital where we're creating agile teams, having very predictable models and being able to get new solutions to market and iterative timeframes. Traditional marketing teams don't typically work that way. So I'm seeing the conversions of marketing and digital. When you think about AI and certainly personalization, where we're creating autonomous, I wouldn't even call them campaigns per se, where we're creating experiences where you're letting the AI drive what that might look like. I see the convergence in the workforce there. I'm certainly well beyond that, but that one comes to mind.

Jason Schlitz (17:52):

I'm just curious, can I get a show of hands? How many folks have had, let's just say in the last year, a new AI tool deployed to your desktop like Microsoft Copilot? Okay. Now of you holding those hands up, how many of you got any sort of actual training or guidance from your company on what to do with that? Right,

Mary Ellen Egan (18:16):

That's a good point.

Jason Schlitz (18:17):

Much fewer, right? I'm also hearing that as a common theme this week. So a couple things that I'd like to speak to that end. One is I feel like we're all being expected to adopt AI in our day-to-day workflow without any guidance or governance on how to do that. And when you think about banking in the regulated industry that we're in, that's a huge challenge. And I think a lot of us are afraid to do much with it, at least on our work computer, because we're not allowed to use, for instance, Chat GPT or some of these other standalone AI tools, but then they've opened up access to Copilot and maybe some other tools. 'Well, how come that's okay, and that's not?' And I think that causes confusion. So I think the other point is we need to start thinking about dedicated AI teams at the banks. If you don't have someone at your bank somewhere in their title it says something of AI operations or AI research or AI experience or something that should be looked at, that's hugely important because these changes are happening faster than we can even realize. So I think those are kind of the two key points.

Wes Hummel (19:31):

Yeah, I think it's interesting because you talked about the training and how I was not at all surprised to see almost everybody's hand go up on your first question and almost no one's hand go up on the second question. Yeah. What's interesting is though, the best analogy I can think of is a plane has landed on the Hudson and you've got to get people out of the plane. And so they kind of show you the cards and they tell you, 'here are the exits' and 'you've got to open the door.' And no one's really paying attention to that. We're in the Hudson now, and there's no doubt we got to get people out of the plane. And so it's like this race, there's not going to be the time for the training. There's an absolute need to go as quickly as possible. But in a measured approach, you talked about data management.

(20:15):

Data management's not only getting important from a security and a regulation standpoint, but also from AI is working on the data that you have. And so if you have garbage data, your predictions from AI are going to be garbage. And so it's going to be really important to not only manage your data from a security standpoint, from a regulatory standpoint, but it's going to be super important to make sure that the integrity of your data and the validity of your data is very good. And from a workforce perspective, as I said, I have three daughters and I tell them, one of them is in animation, one of them is computer science, and the other one's in psychology. The psychology one, she's getting her PhD in psychology. She hasn't yet talked to me about AI. I'm sure it's invading that space as well, but certainly my computer scientist daughter and my animation daughter have said like, 'oh my gosh, it's coming after our jobs.'

(21:15):

And I've said, 'it absolutely is a hundred percent's coming after everybody's jobs.' And so the ones that will survive are the ones that understand it the best, that are self-training, figuring out the applicability of it for their roles, for their company, and ultimately for their consumers. And we talked about meeting customers where they are not being creepy and giving them customers will feel cared for when they do get the relevant, they don't get the buy now pay later. I get so many, I'll buy something and then for two weeks I'll get ads for like, 'do you want to buy this?' 'No, it's a telescope. I don't need two telescopes. I'm good.' And so there's such a gap and one that will easily be closed very soon with AI, but it's going to be critical that we manage data again, securely from a regulatory perspective, and most importantly, from a data integrity perspective.

Mary Ellen Egan (22:13):

We spoke a little bit in our prep call too, about 1033 and open banking and the regulatory landscape. Jason, do you want to start and talk a little bit about your thoughts or what we think might be coming or not coming down the pike?

Jason Schlitz (22:26):

Are you talking about regards to 1033 open banking? Yes.

Mary Ellen Egan (22:29):

Or in general?

Jason Schlitz (22:30):

Yeah. So I mean, as we know, the big news last week is at least sort of officially 1033 is on hold for now, and the Kentucky Bankers Association lawsuit has some teeth in it. So we'll see what happens. But look, regardless of what happens with 1033, we can't control that. Open banking is here, it's here to stay. It's happened in other industries. It's going to happen in banking in the financial industry as well. So we have to look at ways to embrace it, and again, how do we make that experience personalized and something that our customers can get a benefit from versus just shoving another thing to them because the government says that we need to. Right.

Kristen Rankin (23:15):

Yeah, definitely the same. I won't speak to the regulatory aspect, but customers, we do view it as their data. So how we use it and how as a financial institution, we provide value as part of that and partnership with others to carry that forward. So I agree with you. It's here. So embrace it and drive the best experience we can.

Wes Hummel (23:39):

Yeah, I mean, at MX, our position has been, with all this turmoil around 1033, our position has been, 'well, okay, if it ends up being a regulation or not, this is the right thing for consumers.' We believe in consumer permission data, 'you own your data, you should be able to determine who uses that data.' And so when all the rumblings started coming around like, 'Hey, this 1033 is going to go away,' 'are you guys worried at MX?' We said, 'no, actually that's the stick part. But we believe in the care part, which is we do believe in consumer permission data. We do believe that this is the best thing for consumers. We do believe that they should know when their data is being shared with other entities.' And so for us, our data access product embeds all that in there and is the right thing to do for the consumer. And so regardless of what happens with the regulation, I believe what we'll see is a continued momentum towards open banking.

Mary Ellen Egan (24:43):

And I think your point too is because if I find my data's being shared, I'm going to leave that bank. If I know somebody else is going to safeguard it or ask my permission or use it more wisely, then I'm your customer for life. So I think that's a really important, regardless of whatever the regulations may say, it's how do you care for your customers? So before we take questions, any final thoughts? Predictions, where are we headed? I mean, it's a wide open space now.

Jason Schlitz (25:12):

If I make a prediction today, it'll be wrong tomorrow. That's how fast it's moving.

Kristen Rankin (25:18):

I mean, I think you pointed out that final comment around trust. So trust, experience. So two most important things for our customers.

Wes Hummel (25:25):

Yeah, I would just say AI, unlike other technologies that we've had in our history, internet, mobile, those are technologies where, and being a technologist myself, where most times you had a second mover's advantage, you wanted to wait until others kind of took their machete to the path and forge their path through the jungle, and then you go after them. AI is different. It is a technology where you have a distinct first mover's advantage. It is an area where we are doubling down and making sure that everybody understands it and not AI for AI's sake, if you're doing AI for AI's sake, forget it. But if you're keeping your goals and your outcomes the same or even elevating them, but then challenging your teams to figure out where they can use AI to make step function changes in achieving those outcomes and goals, that's the right path. I believe this conference next year will be phenomenally and fundamentally so different than it is this year in ways that none of us can predict. The sessions will all be different. AI is not something that, 'oh, six months from now, it's going to be a little bit better.' It's like it is going to steamroll in very good ways if we use it right. And so that's what I'm excited about, but also very curious to see what happens.

Mary Ellen Egan (26:58):

Questions? Do we have any questions from the audience here? I'll hop down. Sorry, we don't have a no. Runner, I think went to the restroom.

Audience Member 1 (27:16):

You guys talked a little bit about comparing to retail for a lot of different ways. You also mentioned that I think the average customer has three plus different banking relationships. I'm curious, I feel like in the retail sector, they've done a really good job over the past 10 years building really integrated customer loyalty programs. Are you guys building anything like that inside of your banking institutions to try to keep more customers from not having three plus banking relationships versus enabling the money movement between all those accounts? Like you mentioned earlier, kind of curious from a customer loyalty, what you guys are doing in that area.

Wes Hummel (27:55):

I mean, can, I'm not at an institution, I'm at MX, but what I can tell you, we've done, we had a recent hackathon, and although I didn't impose everybody use AI, it was interesting to see that all. But I think one or two of the entries out of 20, some used AI. And one of the interesting one that relates to your question is one team said, 'Hey, if someone wants to buy someone else a donut, who's the most likely to buy another person a donut?' And so if you think, and it was just stunning how AI figured out what are the characteristics? 'Do they visit Dunkin' Donuts? Do they visit Starbucks? Do they do more than once a month?' And it was just their own heuristics. It was not something we programmatically said, 'use these heuristics.' And so I think when it comes to offers, that's where we're heading with our thought process at MX around AI and data is exactly what you're talking about.

(28:52):

It's like, 'how do we better integrate offers?' Because I have a lot of financial apps, way more than I should have, and a lot of the offers I get, there's just certain relevant or important to me. And the minute they become really relevant to like, 'yeah, I go there all the time, I want that.' And it is integrated into the experience where just the normal way that I pay it automatically gives me the discount, then you're going to have some really great magical moments for consumers. And so I think the utilization of the data and using AI to do that is going to be critical. And I do see more and more institutions building this into just into how they interact with their customers.

Jason Schlitz (29:33):

I think part of that is understanding your customer and understanding why do they have those multiple accounts to begin with. Loyalty programs are great, and we have one, and we're piloting a new product right now at Woodforest, but that's not so much about losing customers as it is about acquisition and growth. If we're talking about losing customers, going back to the core business problem, what is the problem that we're trying to solve? And we see these customers opening so many different accounts. Sometimes it's because of a loyalty program, like a great savings account, but I'm hearing a lot of technical challenges, ease of use. It's easier to transfer money within a bank versus using a third party app, or this bank has Zelle now, but this bank doesn't, right? Huge shift lately. So I think those types of technical challenges probably are weighted heavily more to why people are opening multiple accounts to service their needs versus just grabbing the latest and greatest loyalty program that they can find.

Kristen Rankin (30:41):

Yeah, I think it depends on your bank strategy. So we're certainly taking a look at primacy. What percent of our customers are we the primary bank? And it depends on your strategy. So Regions is a regional bank and the relationship is hugely important. So digital plays a part of that. But again, it's sort of that connecting information to a conversation is important. So it's around the solutions. How do we make it easy to switch banks? I think many banks are looking at that now and looking at providers in the market that support that. But I would say not as much loyalty programs per se, but looking at attrition and why customers may be leaving and how do we attract new customers and keep them.

Mary Ellen Egan (31:21):

Unfortunately, we're out of time. Thank you, Wes, Kristen, and Jason, I'm sure that if you, they'll be here for a little bit afterwards and you're going to ask some questions. And thank you all for attending.