595 What if the race for the future of finance is a relay
[Speaker 3]
Welcome to Breaking Banks, the number one global fintech radio show and podcast. I’m Brett King.
[Speaker 1]
And I’m Jason Henricks. Every week since 2013, we explore the personalities, startups, innovators, and industry players driving disruption in financial services.
[Speaker 2]
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. This week, Greg Palmer and Theo Lau joined Brett, Jason, and me, and we’re going to pull apart the headlines and put the pieces back together.
Traditional banks have booked over $268 billion in profit in the U.S. alone, but loan growth limps along barely at 1% a quarter. Venture funding for fintech jumped back above $10 billion, but asterisk there too, because there was a single mega round for Binance. So, the scorecard so far at just about halftime reads banks are fat with earnings, yet hungry for growth.
Fintechs are rich in ideas, but starve for capital. Add in a regulatory microscope on banking as a service and a real-time payments land rush, and you’ve got the makings of a knife fight over who owns the future of money. Now, part of that future certainly has to do with AI, and Theo, you just wrote a book on that.
So, I’ll give you first slash here in the knife fight. What’s the future of money look like, and where is AI going to play? Let’s get past the hype.
What’s the real stuff that’s happening?
[Speaker 4]
I think everyone is either trying to figure out what to do, or they’re pretending they’re doing something, because otherwise it would be fear of missing out is too much. Jokes aside, there are some legitimate use cases that banks have been pondering about. There are some real things that banks have implemented as well, but I think we are still touching on a little bit on what can be done.
There’s a whole long road ahead of us.
[Speaker 2]
Yeah, for sure.
[Speaker 4]
One thing to watch on that, I would say, is look at who will end up winning towards the end. Are we looking at the big banks who have a lot of cash, a lot of resources, but more siloed structure, or are we going to look at some of the younger and smaller financial institutions who are nimbler, less people, but they can find a different model to make things work?
[Speaker 2]
Well, you hit on something important there, the siloed structure, because this is not really a whole new book, even though you’ve written a whole new book. It’s just a new chapter, because it’s the same story about how do we leverage our data for a traditional financial institution. Jason, you’ve been thinking and writing about this a lot lately.
I mean, how far into the game are the banks, and maybe we should bifurcate that. Where are the leaders? Where are the learners, and where are the laggards in all of this?
[Speaker 1]
Well, I’d love Brett’s perspective on this, too, but as a whole, I’m disappointed with both the banks and the fintechs at both the level and pace of innovation. We’re seeing some okay things around. I think, to Theo’s point, AI opened up some, but let’s even just look at it.
Klarna went all in on, we’re AI for everything, and now we’re like, oops, just kidding. We need for lots of things. Then we see we’re all in with some of the banks to go do something innovative and stable coins, but no one can really conceptualize.
What is that? If I hear one more, oh, it’s really good for cross-border, it’s like, oh, how big is that use case for this right now? There’s a level of buzziness that I’m not super thrilled about that the worst show back.
Monarch just raised a monster round. It’s like, really, PFM? We’re back to 2014?
We’re crushing it. We’re just not seeing, in my mind, the level of substantial innovation that I’d like to that actually changes the nature of the business.
[Speaker 2]
Well, you’ve taken us back a few chapters in that same book because that’s the data. We have data on our customers and how much they own, what comes in, what goes out, where it goes, when it goes, but how do we do something valuable with it? Greg, you have seen this from all angles.
At Finnovate, you just came off of the spring show in San Diego this year. How do you connect the dots between the PFM rush of over a decade ago and the AI rush today? Where’s the truth and where’s the hype?
[Speaker 1]
Yeah, so I think when I look at AI, obviously, we’ve seen just an ever-increasing uptick of the number of demos on our stage that are using AI, that are talking about AI, and maybe, to Theo’s point, some of them are maybe talking about it more than they’re actually using it, but it is a phrase that you need to be able to say. I look at it along the same kinds of lines as any other big leap forward in terms of new technical capabilities. People spend a while trying to figure out, what can I do with this?
I think we’re very much in that exploratory phase. It’s more, what is possible? This last show was the first time that I saw people who really started to answer this question, why do I need this?
Where should I be pointing this at? It’s interesting from a technology standpoint. Obviously, from a fraud standpoint, there are certain demos that have a way of capturing everybody’s attention.
Theo, I know you’ve done this on our stages before, showing here’s what a deepfake looks like. Here’s how quickly we can replicate you and make it something that sounds like you, that looks like you. That type of hype is always going to be there, but now we’re seeing people who are taking it and turning the corner.
I think that in another couple of years, it’s going to be the same way. We don’t talk about people using the internet in demos anymore. It’s just ubiquitous.
It’s just something that everybody does. I think very soon, we’re going to be in a position where you don’t actually talk about the AI components of it. The question that matters now is, what are you using it to do?
What problem are you solving? I’m starting to see some creative solutions to that, which I think is really positive. At the same time, we’re a long way from what I think a finished product will look like.
Now, with the pace of AI, who knows? It could happen within another six months. I fully believe that things could move very quickly here.
Right now, we’re really just starting to see people solving real-world problems with it. Some companies at Finnovate Spring rose to the top because they’re able to make a really compelling case. Here is what I’m doing with it.
Here’s why you should care. Here’s why your CFO should care. Everything goes through the CFO at some point.
If it doesn’t make money, it’s not going to happen. That’s my perspective on where we are right now. I was a little overwhelmed at Finnovate Spring with the AI for compliance and not a lot of ability to get depth below that.
It’s kind of like AI can be very impactful. Also, compliance is a big issue. I would characterize we saw a lot of either point solutions that went very deep in something that’s very narrow or the, oh, this is a platform that can solve all of the things for you.
I don’t know that anyone wants to buy a single platform to solve all things compliance, nor do they want something that is so narrow. Also, by the way, it’s still getting charged as if it’s enterprise, but very deep on just one part of the topic.
[Speaker 4]
I would say caution against anyone who can say I can solve it all. I don’t think anyone can. But, Greg, to your point, I vividly remember the first time I chaired the AI track in Finnovate.
That was back in 2020. Finnovate Europe, Berlin. That was the first time I did that.
Now, if we look back and then look forward, 2025, five years have passed. I have witnessed how the conversation has changed in your conference to a point where in the very beginning, it was a lot of what could we do? Well, maybe not.
Maybe yes. Well, maybe we’ll stick in the back and see what happens. To this year is the first time I actually see people come out and say, this is what we did, and this is what worked.
This is what did not work. Now, baby steps, but I’m okay to take baby steps in some things.
[Speaker 3]
I think if I can jump in, one of the things to keep in mind here is we have never seen a technology that has both the growth and the potential for exponential growth that AI gives us. Looking at where it’s at right now is not really a good indicator of where it’s going to be in 18 months or two years time. Now, we refer to Moore’s law as a metric for measuring compute power performance improvements.
We’ve had that since the 60s. Well, AI is improving at the moment at 10x of what Moore’s law is. The ability for that to come in from an infrastructure perspective and reshape financial services is huge.
It’s going to reshape every industry on the planet. The question is who are going to be the players in really utilizing this tech? The core problem the banking sector has right now is that from an infrastructure perspective, if you want to change and put AI-based infrastructure in, particularly for incumbents and so forth, you’ve got a lot of technical debt.
You’ve got mainframe systems and siloed systems, and you’ve got to solve that architectural problem even before you can start thinking about implementing AI. Whereas at least the fintechs have new tech stacks and inserting AI capability into their cloud stack is going to be a lot easier. I think you’ve got infrastructure players like MasterCard and PayPal and Visa who announced their agentic AI initiatives recently.
I think that’s a no-brainer. Klarna’s experiment is an interesting one, but the fact that they’ve stepped back from AI is not an indication that AI is going to fail and not work in the space. It’s just part of the learning process.
I think the key problem I would be looking at now is everything’s going to be AI-enabled in the future. That means that you have to have a culture of experimentation and adaptation, and you have to have the technical agility to do that. They’re the two things that are the biggest problem set for the incumbents.
[Speaker 2]
Do you think that the massive hype cycle around AI and, again, on the latest version of cryptocurrency, meaning stablecoins as Jason brought up, does that starve real innovation in terms of problem-solving for others? Because everybody’s just chasing the technology trigger rather than solving the real problems.
[Speaker 1]
I’ll take a swing at that one. You go, Greg. I don’t think so.
I think that this is one of those areas where you have to try a lot of different things to see what works. I think at a very high level, looking at artificial intelligence from the standpoint of, let’s point it at things that people generally aren’t very good at, things that human beings struggle with. I think this is one of the problems of the industry, is that there are actually quite a few different problems that fit that bill.
If you dig into it, you think, actually, human beings are really poor at a lot of the individual aspects that make up running a financial institution. We have bias that impacts our credit decisioning. We struggle to be cheerful and respond to customers for the 120th time that day, whereas a robot is able to do it perfectly every time.
If you hold it up to this metric, where do people low-key suck at their jobs? Where can artificial intelligence help? All of a sudden, you’ve got this really massive universe of possibilities that you can point it at.
I think right now, that universe is almost too big. You need to start trying some things, throw some spaghetti at the wall, and see what sticks. I think that this is a necessary part of the process.
We forget, when you look at how people engage with all of the different mobile hardware that we have now, there was a time at Finnovate where people were demoing off of a Google Glass. If you even remember that that piece of hardware existed, there was a time where people were looking at all this in-branch hardware, and all of those were good ideas. They were objectively impressive pieces of technology.
They didn’t end up going anywhere because there ultimately wasn’t a real-world need, but in many cases, those were stepping stones that built to something where they found a real-world need. I think that this is a really important part of the process right here. We just have to try a lot of different things.
Not all of them are going to work out. Probably not most of them are going to work out, but this is the path to get to those areas where we can really find the concrete value. I love the example of the Google Glass, Greg.
I think part of the challenge, if we use Klarna as the example, maybe we’re talking it too definitively right now. It’s the mic drop moment. It’s like, aha, all in on the AI, all of the AI.
Back to Brett’s point, it’s like, okay, but there’s an evolutionary process here to really actually solve something substantial that what we really are throwing against the wall first is probably unlikely to be the thing that sticks in the long run.
[Speaker 4]
But Jason, perhaps it could also be they are the ones who scream the loudest, right? There are tons of other startups that have been experimenting with it that aren’t just not making so much waves. There’s Bunk, for example.
They’ve done a really, really good job using AI in the backend with NVIDIA stack for fraud detection. There are a lot of other companies that are doing good stuff. The reason why the Klarna’s of the world and the Spotify of the world were making waves probably not in the best possible way is because it’s crazy.
I mean, it’s no different than, what was it? There was another startup recently on Tech Crunch that they said their whole mission is to replace every single job in the world. Now, are you saying it just so you can get attention or do you actually mean what you’re saying?
There are different intentions.
[Speaker 3]
Klarna’s upcoming IPO is definitely part of the decision matrix, right? But I think if we look at four or five years and you look at where this is likely going to be, the big effort, particularly with agentic AI, is going to shift to more industrial applications, where we can automate business, right? So autonomous business operations, autonomous supply chain and so forth.
I think the thing to keep in mind for this, and we’re already seeing significant development of this in China, US is a little behind on this, but you can’t run that type of autonomous business that we’re looking to build on traditional banking core systems, on traditional payment rails using fiat currency. None of that is fit for purpose for what we’re going to be trying to do with AI from an industrial perspective or a commerce perspective. So there’s only one way this goes, really.
And the experimentation now is to find what is workable as a bridge in the short term while we build these new platforms. And I know Jason’s a big fan of what Stripe has been doing. We’ve had Simon Taylor on the show a few times talking about that.
I think they’re the types of people to look for in terms of what’s happening next, right?
[Speaker 2]
Well, that’s another chapter in this long book, payments. So this is a long chapter. This has been coming for quite a while now, FedNow, we finally have a thousand banks signed up for that.
But at the same time, the same kind of rules apply. Okay, now you’ve got automatic payments, so what, right? Customers aren’t necessarily looking for real-time payments.
They’re looking to use those payments to solve some problems. So I agree with you, Greg, and I agree with really what all of you are saying, which makes this a really boring show. We should fight about something.
But there are two different paths here. And Brett, you have been thinking far outside the banking industry for quite a while. Some of the topics you’ve had on The Futurist Show and so on are really show what the future of this is.
But we have an incumbency of traditional financial institutions that aren’t going to go away anytime soon.
[Speaker 3]
With regulation that reinforces a lot of that too, right?
[Speaker 2]
Yeah. Yeah. And that’s what the tension is when we talk about thin tech, right?
The intersection of those two, there’s this massive growth happening on the tech side. And these governors that restrict growth on the other side, and not the least of which is those pesky human beings who low-key suck at a lot of things, as Greg says. And including not wanting to be replaced with AI.
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Learn more at AlloyLabs.com. Alloy Labs, banking unbound. So let’s talk about the traditional financial service side for just a moment.
I mean, what is the motivation to change faster than they already are when they’re still generating an awful lot of profit?
[Speaker 1]
I think we’re actually starting to see the realization by a good number of them that they can be replaced. When you look at the existential threat of the Stripes, PayPal, SoFi, Amazon’s embedded payments, that some of these big players, it’s not the startups that are going to kill them. They’re just kind of nipping at their heels still.
It’s some of these biggest players that I think pose the greatest threat. And there is enough existential threat that some of the more innovative banks, not always the biggest, are the ones looking at that and say, if I’m not on the front end of it, this could be catastrophic for me.
[Speaker 2]
And that’s something you said 10 years ago. You said, keep your eye on the big companies that are going to utilize this technology, maybe acquire some of the early experimenters of this technology and put it into a place where scale really matters. And yeah.
So for, again, same sort of thing in traditional financial services, unique somewhat in the U.S. with the number of banks that we have, but we’ve got a handful of really, really big banks that are making really, really big investments and they have really big scale. And we have a whole lot of other ones that can’t compete at that same game. They have to be able to leverage this technology in a different way to be able to be closer to their customers and to be able to win on that axis because they’re not going to win on scale and cost.
[Speaker 3]
Although, JP, you know, it needs to be said that there is, there has been a reshaping of financial services, particularly for retail. You guys have heard, I mean, you probably heard this stat from me before, but in the research for the new book Branch Tomorrow, which comes out in September, we looked at the top 20 retail fintechs globally and the top 20 retail banks globally to do a comparison. And it’s not even close, like, you know, in terms of growth in this area.
So the top 20 retail fintechs, they have 4 billion customers amongst them. The top 20 retail banks, 2.7 billion. And the growth is still, like, if you look at NewBank and WeBank, you know, and Revolut, you know, they’re, you know, NewBank’s the largest bank outside of Asia now.
WeBank is, you know, in the top three banks in China for customer numbers. Yeah, they don’t have the asset size. Revolut is, you know, going to be the largest bank in Europe at some point in the next few years.
You know, that’s the reality of how technology is already shaping sort of the experience. And you overlay AI on that, and it would not appear to be a clear supporting element for incumbents in terms of that battle, which is sort of digital and technical competency, which is the way we just do banking now. And, you know, you could argue commercial banking might be different and so forth, but that’s where the whole stablecoin stuff and smart contracts and things come into play, because that’s the type of infrastructure we’re going to need for autonomous, you know, banking at that level.
[Speaker 2]
Well, and it’s not just that. I laughed when you mentioned commercial banking, because what we have seen is a lot of banks kind of give up on the consumer. Hey, we can’t compete in that space.
But boy, that, you know, midsize commercial bank customer, they love us, and they need our capital, and we have these human relationships. And as we talked about on the show a couple of episodes ago with Sam Rasab and with Alex Johnson, what he called the small business operating systems, that technology is working its way into their workflows. So the idea that you run your business, you’re embedded in the workflows of your business, oh, by the way, now I got to go out here and deal with a bank, those days are ending very quickly.
[Speaker 3]
Platformification and agentic AI is just going to turn that stuff on its head. Yeah.
[Speaker 2]
Greg, I’m curious on that point, what are you seeing in the last couple of shows and applications you have coming for upcoming shows in the, let’s call it mid-market space, not just small business, micro business, but established commercial businesses, are you seeing anything interesting in that space?
[Speaker 1]
Well, I think the pithy answer is, is anybody, or is there anything interesting in that space? I think the more substantive answer would be, not a ton, to be honest with you. You know, I think this is one of those things where people who tend to come to Finnovate look either at really small businesses, that’s obviously an area, a segment of the population that needs a massive amount of help.
And again, you know, these are people who come into this because they have a passion for something. I want to be a really good chef. I want to be really good at building something, and they don’t necessarily understand the financial side of things that well.
And so there’s a massive need there. It’s a need that’s easy to quantify. It’s easy to explain.
And it’s easy to, you know, in the context of a seven-minute demo to kind of say, hey, here’s where we can help you here, here, and here. I think when you start to get into the more complicated, you know, more, let’s say mid-size companies, then they typically would have somebody who has more of the experience necessary, right? So we’d need a little bit less of this very basic handholding, and we’d need a lot more of the kind of what’s under the hood.
What are the things that I can do now? And I think this is one of the big problems that we have is just the different levels of knowledge among customer bases in terms of who is prepared to actually use these tools to the full extent that’s possible. You know, somebody who is at a really early stage, a very small company, they can use this very surface level.
You know, we can just dip into the top, you know, 10% of what some of these tools can do and be really happy just living in that top 10%. Some of the people who want to really see the value of it are going to start to dip down and really maybe a couple people will be in a position where they can use all or even most of the technology that’s available. So from my perspective, what I see is, you know, there’s a lot of companies on tech side who are really competing with what’s possible down here when you start to really look at the power of these tools.
But most of the customers are still just at this top level. And so it becomes really difficult for somebody to differentiate and say, my tool does this thing better than yours, but only 5% of customers are ever actually going to use it to the extent that they can notice that. And so that’s, I think, one of the areas that we have to be really careful of as an industry.
FinTech nerds can understand a lot of these things better than their customers can. And so for me, it always comes back to, can you articulate to somebody who doesn’t have your background? Can you tell them why they need your technology, how they would use their technology, how it impacts the bottom line?
And that for me is still the biggest struggle. We’re able to build things much more efficiently and more complex than we’re able to actually talk about them or get people to understand the value. So that’s, I think, the next really big step is, how can I not only build something cool, but can I explain it to you in a way that makes you realize I want this?
And then eventually the critical threshold of now, I don’t think I can live without it. Yeah. Well, Greg, building on that, it might be an even bigger gap, not just explaining it, but getting you to be able to utilize it, especially when we get into these things that around, you know, blockchain and AI that are deeply technical, that people may never actually be able to fully understand it, but they need a product delivered in such a way they don’t need to understand to want to use it and it becomes something they can’t live without. Yeah.
And I think one of the things that we saw at Finovate Spring was, you know, we had a speaker who got up on stage and who was going through, it was an AI presentation. His name was John Lakefish. He was really fun to listen to, but he was talking about things, you know, how to use kind of basic AI tools in a day-to-day life.
And, you know, he was going through things like, here’s me on chat GPT. Here’s me creating these different pieces. And he did them live on stage in a way that was fun to listen to.
But I was looking at the audience during that. And it was clear that for most of them, they really didn’t have very much grounding at all in terms of here’s how I would use this tool. And until you get people who are experienced enough to understand, again, not just what’s possible, but they need to start imagining themselves using it.
Where would I use it? How would I use it? What benefit do I have?
And so this is one of those areas where I think there’s still a lot of work left to do. And I think, you know, as people start to understand more what AI is, you know, we start out with this question of, hey, I’ve got AI, who wants it? I think the critical step right now is more kind of let the conversation go the other way.
Let me, as an innovator, listen to the banks. What are you looking for? What problems do you actually have?
And then I can solve that problem. And you don’t need to care how I did it on the back end. You just need to know that I’ve taken something and made it, I’ve taken a problem that you had and made it disappear.
So I think at this critical moment, we need to actually spend more time listening and less time kind of prescribing. And so many of those conversations can be really valuable in terms of helping these innovators decide, where do I go next? Where do I point this really powerful tool that I’ve built?
[Speaker 3]
Well, more time experimenting. You know, I think that’s the, like, that’s a key takeaway, Greg, from what you’ve just said is, you know, I say in my talking head stuff, I say there are two types of people in the world today. Those who are experimenting with AI, trying to figure out AI, how to figure out how to use it, how to figure out how to put it in the business, you know, you know, thinking about the world, you know, that that AI is going to create.
That’s the first type. And the second type is those are going to be replaced by the first. And I think it’s like, you know, your description of what you see happening in an audience of innovators, a good illustration of the problem set in the real world today is, you know, AI is going to make all these changes.
But if you’re not experimenting with it, if you’re not using it personally, how do you relate to what’s happening?
[Speaker 1]
Yeah, well, and I think hopefully they all have young relatives, right? Somebody who is going to come in and tell them like, hey, here’s, here’s what you can do with this. Well, and I do have to highlight one demo in particular, because it was a voted best of show.
But it was actually the first time that I got spoofed. There’s a deep, deep fake of myself that was played up on the main stage, which was a very surreal experience. Anybody who does work in podcasts, your voice is everywhere.
You guys are going to if you haven’t experienced this, I’m sure it’s going to happen to you. But those are the types of things that really get a ton of attention, right? Someone’s like, oh, man, there was a video that showed Greg, but it wasn’t really Greg.
And so you can kind of scare people into paying attention. And obviously, the fraud implications of deep fakes are really easy to see defending against them seems really difficult, maybe potentially is really difficult. But I think there’s people don’t see AI in terms of the benefits.
Most of the time that it shows up in media and popular culture is something scary is happening. And actually, one of the companies that we’ve got an episode who won best of show called Solda AI, they have one of the metrics that they have is are people aware that they’re talking to an artificial intelligence agent? What is the AI detection rate among people who are using our product?
The implication being that if I know that I’m talking to AI, I’m potentially already a little bit more defensive. I’m potentially already a little bit skeeved out about it. And so I think that’s a really interesting one.
You almost need to flip that script and say, hey, fly the flag. Yes, this is AI, but look at the benefit that it brings instead of trying to disguise it. Now, this is I don’t want to question Solda’s business model.
They know what they’re doing. It was a very compelling demo and Andrew is really good up on stage. But this is one of those areas where you kind of come into it.
You can tell with a defensive mindset. If I’m going to talk about AI, I need to be prepared to say, hey, look, don’t be scared. Yeah, first thing I have to say is always don’t be scared instead of here’s what you can do now that you couldn’t do.
And once people start using it in these little ways that they can start to see the benefit from, I think that’s going to start to shift as well. Although for now, I mean, I will say I’m in that mode where seeing myself spoofed up there was it kind of gives you this squirrely feeling in your stomach, right? It doesn’t feel good.
And so that’s one of those things.
[Speaker 2]
And I had the same thing at our Ally Labs annual meeting. They spoofed a conversation between the two of us that never happened. And they did a pretty good job on Jason, but they really nailed me.
And yeah, it was pretty eye opening. But I think the through line between all the points that you’ve just made, Greg, is jobs to be done. And the thing about scaring somebody is it makes very visceral.
There’s a job to be done to protect my money, to protect, you know, my integrity, all of these sorts of things. And I’m sure you all have seen the meme out there as, you know, the promise was we were going to be able to use AI to automate my job so that we could write and create art. And we’re using AI to write and create art and we’re still doing our jobs, right?
[Speaker 3]
So for now, for now, you know, like here’s the thing is, you know, and using Greg’s lead on this, you know, is we have just, we are seeing models break the Turing test, you know, fairly successfully now, Claude for, you know, GPT, you know, 4.5, you know, we are seeing them perform better cognitively than the average human across the board now. Well, that’s a little more. Yeah, maybe.
I mean, yeah, we do. No, but I’m talking about 160 IQ level. So Albert Einstein level IQ, when it comes to maths and science problems.
Now that doesn’t necessarily translate into being able to take your job yet. But if we look at just where that was two years ago, it does translate in taking your job in the future. So you, you know, you can say right now, Chachapiti is not going to take my job.
But if you’re saying that you just don’t understand the exponential curve, this is on. And that’s the core thing I think we’re saying here is that this change is coming. It’s here.
It’s happening as Eric Schmidt says about it. The fact is it’s, it is going to be a little bit patchy in terms of where this AI is injected into and where it impacts in terms of jobs and industry, but it is going to happen. So, you know, you can sit around and watch that and go, oh, you know, I’m fearful of it, or you can say, I better get up to speed on this and figure out where I fit in this new world.
[Speaker 2]
Yeah. Well, as William Gibson said, the future’s already here. It’s just not widely distributed yet.
Right. That’s certainly the case there. And, and I think one of the things that we talked about at our Alloy Labs annual meeting a few weeks ago was, okay, fine, I get that.
I believe all of that. But you still need some humans to interact with some of those things, sometimes to just sanity check on some of those things. Hey, does this make sense?
And how do we bridge that? Because at a certain point, all of those people are going to be gone and retired. And you’re going to have a generation of people who are, you know, grew up in the world of AI.
So they’re used to asking a black box questions and getting answers. And, you know, maybe those answers are right. There’s a high probability there are, but there’s also enough room for error.
Not that we don’t have human error, but how do we actually, you know, test against those things? And I think, you know, as Brett said, patchy, but I think the way that we bridge to the future is going to be pretty challenging over the next several years.
[Speaker 1]
And I think one of the things that, to kind of follow along with that, one of the things that nobody’s really spending a lot of time talking about is, you know, there are a lot of people with a huge amount of expertise at these financial institutions. And so, you know, to your point, where’s, who’s going to replace those people? Who’s going to come in and bring that kind of skillset to it?
And will they have the appropriate amount of skepticism when it comes to what answer comes out of that black box? Will they have the means to double check it? Will they have the desire to double check?
And so, you know, I think there’s two ways that I think about this. The first one is, you know, artificial intelligence is obviously going to start being more and more heavily relied upon by virtually everybody in society, right? And I think this is one of those things where, you know, whether you’re just trying to write a summary of a podcast episode, hey, give me a quick, you know, two paragraphs on what this transcript was talking about.
There’s these low key ways that you can use it. Then you can start to say, okay, let me have it talk to my customers. Let me have it make sales on behalf of my organization to a point where I don’t even need a human being involved.
All of a sudden, the machine is just like saying, here comes more sales coming in. And this is where, you know, the amount of oversight, I think, is something that people, again, gravitate towards and say, well, who’s double checking in? And that’s a legitimate concern for sure.
Who’s actually going to come through? Who’s the human who’s going to validate things? But I think one of the things that we’ve seen, you know, to kind of play devil’s advocate is right now, the human beings who are checking it are extremely error prone.
And this is one of those things where, you know, my generation, we’re acutely aware. Yeah, there’s bias, but also we’ve seen what happens, you know, unregulated financial institutions. This is my, I’ve been a full-fledged adult now for about a quarter of a century.
And this is, I think, the third once in a lifetime, you know, generational crash that we’re about to see again. We have the subprime mortgage crisis and this is, there were no AI involved in that, right? That was just a bunch of greedy human beings.
So, you know, the, I think all that to say, there are some legitimate concerns out there, but at the same time, what we’re replacing right now is not necessarily perfect by any stretch. And so there’s a significant room for improvement. And so this is where I tend to get a little bit more optimistic about what artificial intelligence can do, because there are, in my opinion, a shocking number of senior executives within the financial industry that, to use my first familiar low-key suck at their jobs, who are in positions where they make decisions with massive ripple effects that they can’t really understand.
So would you rather have a human being make a call on this, on these things, or would you rather have a computer make a call on these things? You know, from a consumer standpoint, I don’t know that it really matters very much. If you can get past this skeeviness, this sort of gut level feeling of something being a little bit off, this kind of uncanny valley type of feeling, then, you know, I’m open to the possibility that artificial intelligence doesn’t necessarily need oversight.
And for all the people who say, you know, deregulate, deregulate, deregulate, I’m a fan of, let’s have a ton of regulation. Let’s let the machines do it and have people whose job it is, external reviewers. So I don’t have to try and replace these people at each individual financial institution, but have somebody who’s looking over the whole thing with the skill set, with the knowledge, and hopefully with some really strong sense of what the technology actually is and how it works.
Because right now, there’s not a lot of people within financial institutions who have that. There’s not a lot of people within regulatory agencies that have that. So that’s a new skill set we need to develop.
But there’s no reason to believe that we can’t start to, people coming out of schools right now, getting master’s in this field, getting PhDs in this field. There’s every reason to believe that there will be people who will continue to understand how it works enough to regulate it. The question is, where does that group sit and how do they actually have any authority over the processes?
But I think it’s pretty clear that as this older group retires and the skill sets are gone, they have to be replaced from somewhere. I’m not optimistic that it will come from inside the bank. I think it almost has to be an external force.
[Speaker 2]
I agree with you. And maybe to summarize that and bring this great discussion to a close, there’s a great quote by Upton Sinclair, it’s difficult to convince a man of something when his wage depends on him not understanding it.
[Speaker 1]
Yeah, absolutely. And so that’s really the thing, where are all of the different motivators? Where are the human level motivators that are going to define how this gets used?
And the people who figure that out are the ones who are going to do really well on the Finnovate stage. They’re the ones who are going to do really well when it comes to engaging that next generation of customers. And they’re the ones who are going to build the right types of technology and point them in the right types of directions.
So this seems like a good place to say, by the way, there is one week left on the Finnovate Awards nomination process. So if you know somebody who’s doing excellent work in this field, somebody who feels that they deserve to be recognized, finnovateawards.com is a place you can go and give them a little bit more publicity. Because we know there are people who are doing really excellent work out there.
And from my standpoint, I’d love to hear more about them.
[Speaker 2]
Yeah. And so will we. I know you’ll have them on the Finnovate show and some of those will probably make their way here.
Well, let’s leave it there. Today, I think what we saw is that the race for the future of finance is less a sprint than a relay. For now, at least, banks are still carrying the baton of scale and earnings, while fintechs clutch the baton of speed and invention.
Profits can buy time, but not relevance. Breakthrough ideas can win headlines, but not always durable funding. The regulators have tightened the track.
The rate cycle is reshaping the terrain. And customers are cheering for whoever hands them the trusted real-time value. So whether you’re building from a 150-year-old balance sheet or a Series A term sheet, the finish line is the same.
Delivering smarter, safer money experiences. So stay curious, stay critical, and try not to low-key suck. And we’ll see you next week on more Breaking Banks.
[Speaker 3]
That’s it for another week of the world’s number one fintech podcast and radio show, Breaking Banks. This episode was produced by a U.S.-based production team, including producer Lisbeth Severins, audio engineer Kevin Hirsham, with social media support from 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.
