Welcome to Breaking Banks, the number one global fintech radio show and podcast. I’m Brett King. And I’m Jason Henricks.

Every week since 2013, we explore the personalities, startups, innovators, and industry players driving disruption in financial services. From incumbents to unicorns and from cutting edge technology to the people using it to help create a more innovative, inclusive, and healthy financial future. I’m J.P. Nichols.

And this is Breaking Banks. Well, this week, we are happy to welcome back to the show, Greg Palmer from Finnovate. Fresh off of Finnovate Spring, have you recovered yet, Greg? Yeah, more or less, although we’ve gone straight into the Finnovate Awards now.

So it’s just, you know, one frying pan into another fire, basically, at this point. Well, we’ll talk about that too. And Brett is here with us, but under the weather.

So I’m happy to be joining you guys, you know, like we haven’t had a chance, the three of us, to be on a show for a while. So I got myself out of the COVID sickbed to do this. Thankfully, we’re not in the studio, I’m remote, you know, but struggling a little bit, but happy to be here.

Good to see you both. It’s great to be reconnecting, Greg, and talking about, you know, Best of Show, as a Best of Show alum. Yeah.

Oh, sorry, I didn’t get that plug in. Yeah. I don’t think you had any time, J.P. You got there right in the first 30 seconds.

I mean, there was no opportunity for you to slide that in. Fair enough. Yes, we are going to talk about Best of Show winners.

And Greg, actually, you’ll, as you do after every show, you’ll actually have interviews with all of your Best of Show winners. So any of the companies and ideas that we’re talking about here, you’ll be able to learn a whole lot more about on the Finnovate podcast here on Provoke.FM. The official Finnovate podcast. The official, one and only.

And so we will talk about that at kind of a high level. But before we even get into some of the companies, let’s talk about the themes and just in general, what’s your takeaway coming out of Finnovate Spring? Yeah. So, I mean, certainly there’s some really interesting Best of Show winners to talk about.

And you’re right. We’ll get into that on the Finnovate podcast over the next couple of weeks. So stay tuned for that.

But I think one of the pieces that’s been most exciting for us looking at early 2024, I guess, you know, first half of 2024 at this point, you know, we had a really strong number of new companies in Finnovate Europe and London. I believe 33 of our 36 presenters, it was their first time on the Finnovate stage. At Finnovate Spring, we saw that trend continue.

We saw way more companies who are at this early stage, kind of Series A, some even earlier than Series A, who are coming across our stage, which is really nice. I think one of the things that we all know about the FinTech ecosystem is that it needs new blood. It needs kind of outsiders to come in and say, hey, we can do things better.

We can do things differently to give everybody a push. And for a little while, it’s been really difficult for companies to get the capital that they need in order to make a concerted effort to kind of drive things forward. Now we’re starting to see a little bit of a loosening of the capital, more companies being founded, and we’re seeing a little bit more of the creativity come back into the ecosystem, which I think is sorely needed.

You know, we saw obviously 2020, a lot of challenges, a lot of kind of inefficiencies were exposed, and there are companies that are tackling those inefficiencies for sure. But it felt for a little while like you’re seeing kind of iterations of the same basic technology. You know, here’s version five of something that I saw, versions two, three and four of, as opposed to here’s something that’s really brand new, a new creative way of thinking about something.

And so, you know, it’s really nice for us to see this resurgence of these new young companies coming into the space. And several of them have won best of show, which is really amazing. But from our standpoint, it couldn’t come at a better time.

We’d love to see new companies and they give everybody else a push. And I suspect what we’ll see after we get a little bit more through 2024, we’ll start to see some of the more established incumbents respond to these challengers by creating their own new innovations. And this is where the cycle really gets fun, right? When you get everybody kind of pushing each other forward, the bar just keeps raising and raising.

So that’s what we’re starting to see right now. And as I said, it couldn’t come at a better time. Well, let’s talk about that cycle for a minute.

How long do you think it takes before we get back around and, you know, the empire strikes back? Yeah, well, the empire always strikes back. The incumbents always come back. Right.

And I think that’s one of the realities. They have such a massive advantage that, of course, they’re going to be able to either acquire companies or design their own versions of technologies that they like. But what we’ve seen is, you know, it typically, in my perspective, is somewhere around kind of a two or three year cycle where we go through these moments where you have a bunch of new companies being founded and then they kind of whittle away, whittle away until you get to a couple who really raise those monster Series C, Series D and kind of get to that unicorn status.

And then we sort of see the process repeat itself where you get another new batch of companies and they kind of fight it out until they’re a handful of winners at the top of the pile. So the big difference is that every time we’ve seen this cycle before, there’s been more and more investment coming from venture capitalists. I don’t know what’s going to happen with the investment rates are growing, but they’re still down compared to where they were several years ago.

That’s maybe where they should be. Potentially, investment got a little bit too overheated and some of the valuations certainly were overblown that we were seeing a couple of years ago. But I think that right now, without that funding, are these companies going to have the resources that they need to go on and really tackle the incumbents? That’s a question that we have to we still have to wait and see.

I’ve heard it from both sides. Venture capitalists are saying, and probably rightfully so, we want to see a path to profitability a little bit more quickly. We want to see you being able to live within your means a little bit more.

But from the fintech side, the truth is that it takes a substantial amount of resource to go out and become a world beater. And without those types of massive Series C’s and Series D’s, will companies be able to get the resources they need to do that, to take on some of these behemoths in the space? I’m not so sure. So we’ll see how this all plays out over the next couple of years.

If the interest rates do start to come back down, I was surprised that they didn’t yesterday. I thought that for sure something was going to move a little bit. But interest rates start to come.

Yeah, not yet. So we’ll see what the venture capital does, because so much is going to depend on how that side of the industry responds. And then, of course, what these early stage companies are able to do with the resources that they are able to get.

I think that this is sort of a classic, if someone’s watching in the industry, particularly from the U.S., but to some extent from Europe as well, that this is sort of the classic industry analyst view of what’s happening, the fintech pause or whatever people are calling it and so forth. But at the same time, we’ve seen some very, very big rounds for some of the established players. Obviously, you’ve got players like NewBank, extremely profitable now, largest bank outside of Asia in the world in terms of number of customers.

You’ve got Starlings just announced their third year of profitability. There’s all good signs there in terms of the investment cycle stuff. You know, we’d have to assume that AI is going to come in and produce a new wave of investments.

And who’s most likely going to benefit from that? Well, the incumbent fintechs, I think, have an opportunity there, more so potentially than incumbent banks, because they’ve already got tech stacks that will be AI friendly, whereas you can’t put an AI on a core banking system. So I still think there’s opportunities for the existing fintech players to get a second round or some support from the AI side. I just think if you, you know, what I find is amusing, and I was on a podcast earlier with Subodh Sarkar, used to be the head of retail for Emirates, talking about this.

And he was using all the classic bank language. Well, fintechs aren’t profitable. They’re not as good at managing risk as traditional players.

And all of those tropes, which we now know are actually false, because if you look at the data, but the one thing that sort of has really struck me in this is if you think about the future world of AI and just even seeing Apple and, you know, intelligence released, you know, in the last week or so and seeing these developments here, it’s fairly inevitable that we’re going to have more and more AI involved in what we would traditionally call financial services. And the organization’s best place to take advantage of that aren’t incumbents, they’re fintechs and still new entrants, right? Because it’s all net new capability. It’s all net new technology.

I just think that, you know, we’re far from seeing the end of this conversation, to be honest. Well, let’s hit pause on the AI conversation, because Maya Mikhailov from Savvy AI, which is one of the best in show winners from Fenovate Spring is going to join us on the show just a bit later. I think that’s a very important through line, but I just want to go back to this is kind of the classic battle of can the incumbents innovate and iterate faster than the insurgents can scale.

So that kind of cycle goes. And Greg, do you think it kind of matches up with what Gartner calls the hype curve? Do you think that cycle kind of follows? You know, we have the peak of inflated expectations, right? Then the was of the trough of disappointment, disillusionment, right? And then eventually you climb the slope of enlightenment. Do you think that kind of factors into the cycle that you’re seeing? Well, certainly, I think there’s an emotional side of it, right, because there’s what companies are doing can be very new and exciting.

But then there’s this question of will they get the first kind of critical partners, the first critical customers who will give them the space to take their ideas out of the lab and put them into the real world. And that’s really where things can get really interesting, really quickly. Right.

There’s a lot of technology that looks great on the stage. And then when you put it out into the real world for one reason or another, it can struggle to gain the traction that it needs to to get past that disillusionment phase, basically. But I do think that what we’re seeing right now is this creativity coming back in, some people focusing on areas that maybe haven’t been focused on for a while.

And so for me, that’s always where I get excited when I see companies that are doing things which nobody else is really doing or which are different takes on something somebody else is doing, because that’s where you say, OK, now you’ve got something which is really unique. It puts you apart from what other people are able to quickly go out and replicate. That’s where I think you can start to see some space between an early stage company and what a company is able to come back in and deliver, because if you get a significant advantage, you’re thinking about something in a new and unique way.

It’s difficult for companies not necessarily to recreate that technology, but to recreate that thinking. And that’s where you can really find some open ocean. So, you know, are we going to see all of the companies who came to Finnovate go on and become unicorns? Obviously, the answer is no.

But the more of this kind of creative pieces that we see, the more likely it is that some of them are going to go and really get some distance between themselves and what incumbents are able to quickly build and follow. So it’s going to be one of those things we have to watch closely. And again, we’re in a really different environment than we have been before.

So even though we have some data that says we know how early stage companies will come in and impact the industry, we’re in a unique situation here and we don’t know exactly what that’s going to look like. But I still think that there’s enough creativity out there, enough of this new way of thinking about things, that it’s going to be difficult for some of the incumbents to pivot and recreate some of those solutions on their own. So that’s where I get really excited, again, about what we’re seeing in the space right now, because that new creative side does create some difference and it will push everybody to do a little bit more.

Yeah, I’m also thinking about just the classic innovator’s dilemma on the disruption curve, right? So once you become an incumbent, you have downside to protect and you’re making incremental improvements and that leaves space for new pain points to arise, new jobs to be done. And it’s the insurgents who kind of pick up on those, wake up the incumbents and go, oh, yeah, I guess that’s kind of a problem. We got to go figure that out, whether they acquire those companies or build it themselves or whatever happens.

So I think that’s a part of the cycle. You mentioned the VC funding cycle. Jason’s been talking about that lately and he’s got some more shows coming up talking about that and how the last hype cycle, if you will, on VC funding has been trying to really engineer some soft landings, Frank Rotman says, land the plane.

And so that plays into the cycle as well. The other piece that’s really an X factor that’s out there is there’s this question of when a company takes a massive amount of venture capital funding, obviously they lose a high degree of control over what ultimately happens to their technology. Those venture capitalists come in and they can push for a specific outcome.

So if somebody comes in and makes an acquisition offer, the owner, the founder might not actually want to sell, but they might feel a lot of pressure from the VC partners to go in. And we need a successful exit here as the amount of funding decreases. And I think I’ve talked to companies who are strategically taking less funding in order to keep more control over their own products and their own ideas.

I don’t know what that’s going to do either in terms of our company is going to be a little bit more hesitant when it comes to getting acquired. Are they going to be more open to acquisition talks? The idea that the founders will have more of a say in that decision is another big X factor. And it’ll be really interesting to see how that dynamic plays out as well.

You know, one of the things, Jason calls it the FinTech petting zoo, but one of the things that Finnovate has been best known for is bringing together incumbents so they can look at these different FinTechs and see if there’s acquisition potential or if they should just copy what the latest FinTechs are doing, that sort of stuff. But I’ve heard anecdotally, and I’d like your observation on this, that there’s less of those sort of players this time. There seems to be more of this, as you said earlier, early stage, you know, sort of more experimental stuff coming back into the mix.

But, you know, is there still that sort of dating game going on between the incumbents and the FinTechs? Or is it a little bit of, you know, that things are changing a little bit and the FinTechs are getting back into this more experimental phase again? Yeah, well, certainly the incumbents are very aware, I think, of what a lot of these early entrants are doing. And I think, you know, a lot of them do come to the event to scout out and see what their potential competition is or if there’s companies they want to make a strategic alliance with. The other really big thing that we’re starting to see is now there’s a line popping up between some of the really large financial institutions and the smaller community banks and credit unions.

And a lot of the companies that we’re seeing on our stage are looking specifically at those smaller FIs and thinking this is a really good opportunity for us to go and help these companies out. Where, you know, five years ago, everybody wanted to go and talk to the director of FinTech strategy at Citibank or J.P. Morgan or what have you. Now we’re seeing companies who are really looking, let me get a local credit union, let me get a community bank, because we know that these are more realistic targets for us.

So you’ve got this kind of playing out in two ways. There’s the incumbent FinTech providers and how they’re looking at the new technology. There’s also the incumbent banks and how they’re looking at this new technology as well.

So the incumbent banks have a really significant advantage, of course, which is massive development teams. They can look at new technology. They can potentially build their own version of it in-house.

And what that’s done is it does make it more of a petting zoo. You know, some of those banks will come in and kind of look and say, OK, here’s I like that. I like that.

I like that. Can we build something that does that functionality? We’re also seeing more community banks and credit unions who are at the point now. And J.P., I think this will be music to your ears where they’re finally starting to recognize, hey, we need to be doing something differently.

We’re falling behind and we can’t keep falling behind. And so we’re seeing them coming to the event less so from a let me stand back here and kind of take a look at what’s out there and more from a let me get in there. Let me go and actually have these conversations with you.

Let me figure out how we could engage with you. Obviously, they’re not able to engage with all the technologies that they want to because of time and budgetary constraints. But there’s much more realness behind some of these interactions.

And so that’s where you’re going to start to see this incumbent versus smaller company line is going to play out in two different dynamics. We had a credit union session specifically for credit union employees because last fall we noticed that there were just way more credit unions coming to innovate. That’s a great thing.

That’s a group who really needs to be there. And they’re not able to build their own technology in-house. In most cases.

And so as we see that group grow, as we see more companies on the other side targeting those smaller FIs, I think we’re going to start to see this line really start to pop up in a couple of different areas. So hopefully we can get past kind of the petting zoo where you just sort of stand back and gawk and say, oh, that’s interesting. I hate that phrase.

People come to innovate and say, oh, that’s interesting. But what are you going to do about it? I’ll give you a cool stat. I’ll give you a cool stat, which I just did for I had a credit union event I did last week, and I was telling them about WeBank in China, in southern China, you know, the largest digital bank in the world, 400 million customers.

WeBank has acquired more customers in nine years than all of the credit unions globally over the last hundred years. We put an asterisk up there, though. I mean, like, oh, yeah, you could put an asterisk, but still.

Well, listen, I mean, we could go on all day about that. And I know Jason ran a session for community banks at Finnovate as well. He’s going to be talking about that.

I’ve been doing this whole series we call Unbreak the Bank. And I think you’re right, Greg, where. We’re getting to the point where most organizations are realizing they need to do something, and now what we need to do is break out of the, oh, my job is vendor due diligence, because the job is really understanding what kind of value proposition are we trying to deliver here, then we can figure out the partners.

But I want to talk about a couple of things before we take a break here. First of all, I want to just finish up on the theme. So we talked about AI, we talked about our earlier stage companies and the hype cycle and the VC cycle and all of that.

I want to know what other themes you’re seeing, and then maybe just kind of a quick high level overview of how those themes manifested themselves through the best of show winners at just a high level. Yeah, yeah. So I think the other theme that I didn’t really talk about so far is looking at FinTech from a much more personal standpoint.

We’re seeing companies now who are looking at some of the problems that companies have been looking at for a while, but looking at them through this lens of what are human beings actually likely to do in these types of circumstances, because FinTech is notorious. There’s a giant bubble around us. People in this space are typically high earners.

They’re people who are good at keeping budgets. And we build these products for people like us. And then the general population is like, well, I don’t want to go in and look at my bank account on a weekly basis.

That’s depressing. That’s going to bum me out. And I think there are people who look at something like debt collection or credit building, and this is an area which causes a significant amount of the population to just kind of throw their hands up and say, ah, I can’t do it.

And now we’re starting to see companies who are looking at this as actually you can do it, let’s build you a solution that kind of takes you by the hand and says, Hey, we can help you build credit. You know, bloom credit is a great example of a company who won best of show. And they take a much more customer centric approach.

And I think this is one of those things that’s really cool. There’s this massive win-win when a financial institution is able to help somebody and say, we can help you grow your credit. Then I can go and lend to you.

I can create a customer that I can then go and win. But in order to do that, I first have to get you to believe that we’re on the same team. And we’re seeing more of that type of technology as well, where you think, okay, let’s get the banks and their customers actually on the same side.

So if I’m about to default on my debt, I don’t feel like my bank is going to punish me even more than that. I already feel bad about it. This is not how I wanted it to go.

I know nobody signs a mortgage or signs a loan thinking I’m going to default on this. It’s a, it’s a bad feeling. But if somebody can come to you and say, actually, let me help you, let me help you come out of this.

And, and remit is a terrific example. Another best of show that focuses on the debt collection space, but they do so from a very human standpoint, which is, you know, we want as an organization, as a financial institution, we want you to pay us back. You want to pay us back.

You don’t want to have your credit score hammered. But if we can work together, we can actually rebuild your credit score. We can collect as much of the debt as we can and come out of it in a situation where both of us have positive feelings about the other.

And that last piece I think is really crucial. This idea that we want people to actually enjoy their financial institution, to feel some sort of loyalty to their financial institution. I’ve heard a lot of banks talking about, you know, I wish my customers were more loyal to me.

And we can’t offer it at the same interest rate that the online bank can pull my response to that as always. Well, what are you doing to earn that loyalty? What, how are you demonstrating that you’re loyal to your own customers? Well, are you helping? Well, you were founded in 1882. Doesn’t that answer it? Right.

Yeah, exactly. If I, if I’m one day late on my credit card payment, are you going to come in and hammer me with a late fee? Because that to me says, Hey, we’re not on the same side. And, and so this is where I think, you know, the industry has a lot more that they can do.

And the good news is we’re starting to see people approaching it, looking at, you know, behavioral scientists on staff, looking at the psychological aspect, and I sincerely hope that continues because there’s so much benefit that can come from that. Well, let’s just, you mentioned bloom credit. You mentioned a remit.

We talked about savvy and we’re going to have a Maya Mikhailov on the show here shortly. Maybe just go quickly through the other best of show winners and talk about what they do, what they presented. Yeah.

Yeah. So, yeah, we did talk about bloom. So cascading AI is another one that is a very good customer service type of AI tool.

And we’ve seen a lot in this space, but there’s is really, really well done. So that’s a, that’s a cool one. Cobalt labs is another one that is kind of a surprise.

They’re a very new company focusing on the regulation, regulatory space. Obviously a lot’s been made over how painful some of the new regulations are. And so Cobalt is directly attacking that problem by making it easy for banks to avoid potential risk there.

And that’s a really cool company. I recommend everybody check out that demo. QuickFi, you may remember they’ve won best of show now several times.

They do business financing and they do it really, really well. They’re all, their presenters are also really good at Finnovate. Now they’ve come multiple times and just watching that team up there.

They, they do such a good job with the seven minutes. But yeah, QuickFi is another one. And I believe, yeah, I think that’s it.

That’s, those are, those are the ones we’ve got. So six, six winners from Finnovate Spring. Well, not only can you hear the deep dive with Greg on the Finnovate podcast, you can watch their seven minute demo videos on finnovate.com. So highly recommend doing that.

I highly recommend going to Finnovate when you can. If you can’t, the next best thing is being able to watch all of these pitches in one place. So Greg, thanks for that quick summary.

Let’s take a break and then we’ll be right back. Hello friends. It’s Brett King from Breaking Banks.

Are you looking for something different? A game changing lesson? Well, I want to tell you about a podcast that we’re happy to support. I really think you’ll like it. It’s called Be The Way Forward.

It’s brought to you by Anitab.org. President and CEO, Brenda Darden Wilkinson is diving into some really incredible chats with tech trailblazers like Arlan Hamilton and Creative Powerhouses like Gin Elmanay. This isn’t just another tech talk, you know, tech bros podcast. It’s a front row seat to the minds shaping our future.

Are you ready to drive the change around AI and digital transformation? You need to be part of the movement. Get plugged in to Be The Way Forward, wherever you stream your favorite podcasts. This show is brought to you by Alloy Labs.

As much as we love talking on the show, we believe that action is more valuable than talk. Alloy Labs is the industry leader in helping fearless bankers drive exponential growth through collaboration, exclusive partnerships, and powerful network effects that give them an unfair advantage. Learn more at alloylabs.com. Alloy Labs, banking unbound.

Well, over the break, Brett has bowed out. I think his bout of COVID here has gotten to him. But Maya, me a love.

No, I still got it wrong. Me high love, right? Me high love. And I mispronounced it horribly, Maya.

I’m sorry. I remember you. And once you go through the phonetic spelling or pronunciation for me, I remembered that you did it last time you were on the show and I totally blew it.

And as Nichols with no H, I try really hard to get people’s names right. So I apologize for that, but really glad that you’re here. And Greg, you were telling me about, not only did Maya win best of show this time, but she had a pretty memorable appearance on the Finnovate stage in New York last fall.

What happened? Yeah, well, so we’ve been aware of savvy AI for a little bit now. And it’s been one of the fun things that Finnovate, of course, is getting to sort of follow companies on their evolution and seeing how they grow in terms of how the technology grows, but also how they position themselves. And when we first saw Maya on stage, she had really amazing technology, really cool AI stuff.

And there was this kind of question over how do we differentiate ourselves from the other AI solutions that are out there? When everybody’s saying AI, we actually have the AI. And I think you’ve done a really good job, Maya, of kind of figuring out how you can talk about it in a way that gets to the value that you provide. But last fall, she came out and said, Greg, I want you to do me a favor.

I’m going to get up on stage and say, we’re going to talk about AI, expecting this kind of audience fatigue reaction of, oh, God, here’s another AI demo. And she actually invited me to throw a tomato at her from backstage and sort of a, you know, oh, boo, here comes another AI demo, as a way to sort of say, we know that you’re sick of hearing about AI, but ours is actually better. And so there’s two things that I think are really fun about this.

Maya, I appreciate the way you’ve been able to grow the technology, but also, that’s the first time I’ve ever gotten to throw anything at a Finnovate demoer, so that will, I will always remember you for that. It was a tremendous opportunity. And I think a great way to start your demo off and really get into, you know, here’s why we’re different.

Here’s how come you need to pay attention to us. So I just had to share that story before I bow out and let you all have your conversation. Well, Greg, having been to well over a dozen Finnovates and had, you know, hundreds of conversations with you, I won’t name names, but I know it’s not the first time you wanted to throw something at a presenter.

Absolutely not. And I won’t name names either, but I think I need to figure out where you got that tomato, Maya. I just have a crate of them backstage, just in case.

Oh, that’s great. That plush tomato sits on my desk and reminds me every single day not to do groan-worthy AI. There you go.

Well, that is a great way to tee it up. And Maya, I did watch your video on the Finnovate website, and I love the way you opened this spring’s demo as well. Could you kind of give our listeners just a quick preview of how, what you talked about and particularly the comparison to JPMorgan Chase? Absolutely.

So just to give you a little bit of background on Savvy, it’s a tool that helps any FinTech or bank build and launch their own goal-driven AI use cases without the need for specialists, without the need for integrations. But then we took it one step further because we kept hearing over and over again from banks, make it easier, make it easier, and we did, we came to where they are and we distilled our entire solution natively into Excel, which means they can stay in the spreadsheets that they absolutely love and still get the power of AI to predict capital requirements, analyze deposit data to find patterns of churn, and so much more. But one of the points I made on stage that I think is really important is that there are banks out there that are succeeding with AI very loudly.

JPMorgan is one of them. They have over 300 use cases in production. They have 900 data scientists, 1,100 data engineers, and they spend a billion dollars a year on AI.

Now that’s great for them. I mean, they’re clearly seeing the success of those use cases, but that’s simply unachievable for the majority of the banks out there. And what we saw, and what we saw at Synchrony even, so I came from Synchrony where I built and led an AI-focused team, is that there is this just chasm growing between the folks that can afford these heavy resource, heavy infrastructure builds, and everybody else.

And yet all banks should have access to these powerful data-driven tools, including AI, with the teams that they already have, and that was our impetus and our mission behind Savvy. Yeah, it’s a great one. And I love the whole idea of we need to meet users where they are.

And as you know, that’s kind of what we focused on at Alloy Labs. And we’ve had the pleasure of working with you through our Alloy Alchemist Fund, and you’ve worked with many of our bank members and so on. So I’ve got a little bit of an inside track here, full disclosure, but I’d love for you to even talk about what that journey looked like.

You know, here’s where we started. We thought users were going to engage with us. Then we thought this, then we thought that, and then sooner or later, you know, it’s shocking, you’ve seen the graphic that’s gone around as a bit of a meme, how it’s like a Jenga, you know, house of cards, and at the bottom of it, it’s a bank infrastructure, at the bottom of it is Excel.

It’s shocking how much bank infrastructure is built on Excel and really kind of common consumer tools. So talk a little bit about that journey of, you know, where you started with a vision, knowing the power of AI and the sophisticated apps and applications and uses that you’ve built and what got you to where you are today and the way you’re focusing it. Absolutely.

Well, because we are a build team at Synchrony, we thought about building tools basically for ourselves. And I like to joke that this is probably one of the first AI companies that instead of crawl, walk, run, ran, walked, crawled. I love that.

We went a little bit backwards, but the reason we went backwards is because when we started Savvy, our hypothesis was, look, if we give folks these APIs, they’re going to figure it out. They’re going to integrate it with their tools. They’re going to run with this because we’ve really taken an entire AI center of excellence, entire cycle from building to managing to productionizing AI, and we’ve given it to them in one simple tool, it could not be easier.

And the feedback we initially got from banks was, wow, this is great. I mean, I understand what you’re doing, but so you’re going to integrate with core now for the next 12 to 18 months. And I think for us, that was a real wake up call that although FinTechs can easily use our API suite and our code tools like JavaScript and our integration tools, banks were sort of hampered by what they could have access to and the easiest way to get that access.

And so as we started talking to more and more banks, we spent a year talking, I mean, dozens of banks, and what we really realized is they were grabbing their data out of their core systems. They’re grabbing it at CSVs, basically like Excel files, and they were spending the work with their data analysts to transform those Excel files, to try to draw data-driven insights out of those Excel files, to try to forecast and predict out of them, so we really realized that instead of being ahead of where they are, we really ought to meet them where they are right now, and if where they are is Excel, there’s no shame in that. We all use Excel.

I use Excel every day. Like, there’s no shame in using Excel, but why not supercharge it with the power of these models that can crank through, you know, your 10,000 row plus loan tape instead of having a data analyst sort of go cross-eyed to try to find insights there, and that was kind of our big awakening is we have to stop building ahead of them. And by the way, JP, I think that that, I’ve increasingly seen that there’s just two conversations happening right now between banks and AI companies, and they’re completely in different languages.

You know, AI companies right now, for the majority, are basically talking about landing rockets on Mars, vectorized databases, hyperparameter measuring. I mean, they’re talking this language of big tech, and banks are saying, how do we increase deposits? How do we become more profitable? And they’re talking right past each other, and we’re hoping that our sheet solution becomes that bridge to get them to the future of here’s something you can start with today, here’s how you can upskill your team today, here’s how you can get there tomorrow. I don’t think that’s limited to just AI, right? Oh, true, a hundred percent.

You know, Greg and Brett and I were just earlier talking about, you know, the hype cycle, right? There’s a new capability, so the market gets ahead of itself. And then when those expectations aren’t met, right, it kind of crashes, but then we eventually climb that slope of enlightenment. And for you, it was, you know, where are our users, what are the tools that they’re using, but kudos to you for making those changes, those adaptations, and not only is it meeting the users where they are, but it’s also understanding the jobs that they have to get done.

And, you know, we see this because we’re in the middle of that every day, right? How do we help community and mid-sized banks be better partners, better consumers of fintech? And you’re right, there’s just so many different languages. And then the other thing that’s kind of simple and trite, but also still true, is the old bromide that, you know, people buy more aspirin than they do vitamins, right? So you have to solve a pain, a pain they know they have, and ideally one they’re even trying to solve in a way that maybe is more painful than the underlying symptom. And so when that’s dealing with the spreadsheets, and like you said, those data analysts trying to sort through CSV files, if you can give them a tool to help relieve that pain, that’s a really good thing.

Yeah. And, you know, we’re hearing three pain points pop up a lot, and they’re very practical. I need to increase deposits, I need to increase profitability, and I need to decrease loan delinquency if I’m a lender.

I mean, we just hear those popping up all the time. And what’s interesting is that when I ask where they are on their journey, forget about AI, of even just mining their own data for insights for that information, many are a little bit stuck in the beginning. They have the data, they know the answer is somewhere in there, and they don’t know how to unlock it.

And whether, you know, AI happens to be just a powerful tool to unlock data because it can plow through so much of it and find that insight needle in the haystack really easily. But a lot of it is just how do I get started? I know I have this problem. I know I need to increase deposits.

I know I need to decrease churn. I’m sitting on all this data, but how do I connect my problem with what I think can solve it? Yeah, I’m really curious on kind of a second order problem there, particularly on the deposit cost, because we are seeing and hearing this all the time, too. And, you know, I’m just going to be like full of all the old, you know, buzzwords and stereotypes, right? If every only camera, you know how to use or tool, you know how to use as a hammer.

Every problem looks like a nail. So for the bankers, they say, yep, we need to gather deposits because that’s the life blood of a bank, right? The very, very core business model is we gather deposits, we mark it up, lend it back out. And to your point, we need to keep the delinquencies down because it’s a leveraged business model.

And what we’ve been trying to dig through is what besides the rate calculations, right? So so part of the use case is, well, how do I understand my price elastic versus inelastic customers? And, you know, what can I do with my portfolio and my duration? And all kinds of really smart people are using all kinds of really smart tools there. But we’re also seeing some very interesting cases of thinking, well, what non-rate value can I bring to my customers in a way that starts to minimize the math, which can only go so far, by the way, right? Yeah, exactly. It’s literally one lever you can only pull so many times.

Yeah, that’s right. So I’m curious what you’re seeing on how people are using AI to find not just, you know, rate sensitivity or, you know, portfolio dynamics, but ways to deliver new sorts of value to customers. Sure.

So here’s a really straight down the fairway use case. Customers that you have might be transferring money out of their accounts immediately when they get their paycheck. Oh, the Ron Shevlin Paycheck Motel.

Exactly. Exactly. But what we’re seeing is a lot of younger customers are transferring their money right away to platforms like Robinhood, for example, where they want a digital wealth product.

And so what you think you’re getting their whole deposit, you’re only getting their whole deposit for a matter of seconds. It’s going right back out again. Now, banks can use AI to find those kind of insights and to determine if maybe they already have a digital wealth product and literally nobody knows about it and they could be retaining some of this business in-house or maybe they ought to offer certain types of products.

And when they see the money leave their platform, that can give them better insights as to the products that their customers want other than just playing around with rates every day. So that’s a simple example of where they already have the data, they already know it’s moving, they just have to do something about it and find those insights so they can make the determination of what’s that next product that they want to offer. Or why aren’t we telling more people that we have X because X is exactly why they’re leaving.

Yeah, it’s the why behind the why and sometimes the why behind the why behind that. I’m working with a bank right now that is thinking very interesting about a certain small business segment. I won’t say too much about it, but they’re kind of looking at what are the customer jobs to be done, right? What are the pains, the gains, kind of classic customer-centered development.

And one of the big ahas that they had early on is we actually have a fintech partner that we bought and vetted and went through due diligence on and are paying for. And as far as we can tell, we have exactly zero adoption for it right now. And so they’re trying to understand why not.

And part of it is they just really haven’t marketed it and probably don’t really even understand it. But who are the customers that need the kind of capabilities that this partner could bring? And so being able to mine through that data quickly would be really powerful for them. Oh, absolutely, JP.

And it’s not about, you know, marketing is not just a panacea if you paint everyone with the same brush. Because the problem is, is that you need to hit the right customers at the right time who are willing to take a product like that. And when you treat marketing as we’re just going to tell everybody about all our products all the time, it gets lost in the noise and the shuffle.

When you mine your data, find the insights of these customers are more likely to take this product. Let’s target them. Let’s appeal to them personally.

Now you have a really interesting campaign. And now you have something that’s probably going to increase uptake versus just a generic banner ad that’s somewhere on the bottom half of your, you know, digital front page that no one saw. Yeah, that’s a whole other channel.

And we’ve been talking about this. I literally, I wasn’t planning on this. I just posted on LinkedIn yesterday evening.

I was looking at what some banks are doing and saying, and I literally came up with, without like looking for it, without mining for it, just eight of the first 10 banks I was looking at in there about us, right? On LinkedIn, they’re the top of the fold, most valuable real estate to tell somebody about who they are, mentions their founding year, right? That’s what I was joking earlier about with Greg, hey, we were founded in 1882. I mean, some impressive numbers, right? One bank founded in 1825, right? A lot of them are hitting a hundred-year anniversary now, right? A lot of banks formed in the mid-twenties. That’s great.

But what does that mean to me as a customer? And exactly to your point of just kind of pushing product, hey, we have this, do you want to buy it? Versus we think we understand you because you have this problem or this opportunity, and we can help you address that by the following. I’m curious, what is the most interesting? So you gave a really good, as you said, down the fairway example. What’s the most interesting use case you’re seeing people, financial institutions use AI to find kind of new value streams? I don’t think there’s only one.

It really depends on what their goals are. I mean, we have folks that are lowering ACH return rates. We have folks that are using this for FP&A purposes for modeling.

You know, JP, I’ll answer it a different way. What makes it interesting is how, quote unquote, boring and practical these use cases are. You don’t have to be interesting.

I think there’s this misconception that you have to be interesting in AI, just like you don’t necessarily want your airline pilot to make an interesting flight decision. You know, I understand that banks don’t want to be interesting sometimes. They want to be practical.

They want to be efficient. They want to take risk into account, trust into account. So, what I think is very interesting that they’re doing is they’re even just getting started, you know, that they’re looking at their data and they’re saying, hey, listen, why have we been collecting data for the last decade if we’re not going to put it into action? And some of these use cases are so behind the scenes.

And I think that’s what’s important to note, too. Everybody is used to talking about AI as a generative AI concept, as a chatbot. But some of the most powerful AI use cases that JP Morgan is using, that Netflix is using, that Amazon is using, they’re very much behind the scenes.

Things just work. They work better. Messages are a little bit more tailored.

You know, efficiency, people aren’t spending a lot of time doing an inefficient non-value add task. It’s these little boring use cases that add up to huge value and are of interest because then that 1920s bank is functioning like a 2020 bank. Yeah, I mean, point well taken.

So, let’s take it from there then. If you haven’t done anything, you’ve got data by definition, right? You’ve got a lot of data. I hope so.

Yeah, it might not be in what you feel like is a very usable form. It might reside in different systems. It might not be, you know, in a real-time fancy data lake or whatever.

But you know how much money your customers have, how much they owe, what comes in, what goes out, when it goes, where it goes. And where should we start, right? If I’m a bank thinking about this. There, right there.

Your deposit data, your transaction data, your action data. This is such easy data to start with. Look, I know there are folks talking about mining unstructured data, like customer service conversations.

That’s valuable too. But you know what you have a ton of? Structured transactional data. And it has worlds of insights in there.

You just haven’t tried looking. So, I think that’s a good place to start. Start with your transaction, your deposit data, your checking data.

Start with your lending data. You can pull so much value out of just that alone. And those are low-hanging fruit.

So, you don’t have to get creative and interesting. You can win right there. Not only is that a good place to start, that’s a good place to stop.

That’s a mic drop right there. Maya, how can people find out more about Savvy AI and or talk with you? Absolutely. They can go to Savvy, S-A-V-V-I.

We couldn’t afford the Y. S-A-V-V-I.AI.com to learn more about Savvy. They can reach out to me at Maya at SavvyAI.com. I’m always happy to talk about AI. And I’m always happy to talk to banks about what we’ve seen work, what we’ve seen not work, and just easy places to get started.

Just get started with the data they have and the team they have seen success. Excellent. Well, thanks for joining us again on the show.

Congratulations on the best you show in. We’ll hear more from you on the Finnovate podcast. So we’ll wrap it up here.

And we’ll be back with more Breaking Banks next week. That’s it for another week of the world’s number one fintech podcast and radio show, Breaking Banks. This episode was produced by our US-based production team, including producer Elizabeth Severance, audio engineer Kevin Hirsham, with social media support from Carlo Navarro and Sylvie Johnson.

If you like this episode, don’t forget to tweet it out or post it on your favorite social media. Or leave us a five-star review on iTunes, Google Podcasts, Facebook, or wherever it is that you listen to our show. Those actions help other people find our podcast.

And in return, that helps us build an audience that can be supported by sponsorship so we can continue to provide you with our award-winning content every week. Thanks again for joining us. We’ll see you on Breaking Banks next week.