Podcast 159 Scott Snyder Fintech
00:00:04 Lisa Hochgraf
You're listening to the CUESpodcast, episode 159.
Welcome to the CUES podcast, where leaders and experts discuss the top topics in credit unions today. I'm Lisa Hochgraf, senior editor at CUES. In this episode, we explore best practices in leading in an age of emerging and potentially disruptive technology.
00:00:24 Lisa Hochgraf
Our guest is Scott Snyder, a recognized thought leader in technology and innovation. He has more than 30 years of experience in emerging technologies, business strategy and innovation and digital transformation for global 1000 companies and for startup ventures.
00:00:41 Lisa Hochgraf
He is the co-author of Goliath's Revenge: How Established Companies Turned the Tables on Digital Disruptors.
00:00:48 Lisa Hochgraf
He is also a senior fellow in the management department at the Wharton School and an adjunct faculty member in the School of Engineering and Applied Science at the University of Pennsylvania.
00:00:58 Lisa Hochgraf
In this show, Scott shares well-thought-out advice about how credit union leaders can make better decisions about how they'll pursue the big opportunities presented by artificial intelligence. It's important to point out that while Scott is every bit a technologist, he also believes that business innovation, especially at credit unions, is ultimately all about people.
00:01:21 Lisa Hochgraf
I know you're going to learn a lot from Scott, so let's get started.
00:01:27 Lisa Hochgraf
Welcome to the show, Scott.
00:01:29 Scott Snyder
Thank you. It's great to be here, Lisa.
00:01:32 Lisa Hochgraf
I'm excited to get to talk with you about credit unions and fintech, but first I'd like to help our listeners get to know you a little bit. To that end, would you have a mantra or a quote that you live by that you could share?
00:01:44 Scott Snyder
You opened Pandora's box because I love quotes.
00:01:47 Scott Snyder
One is more of a saying, but Satya Nadella, who's the CEO of Microsoft to a lot of people, you know, now has a saying that he'd rather hire “learn-it-alls" than “know it-alls,” people that are just continuously challenging and improving themselves versus being stuck in their expertise and what made them successful before. The other one, I love that goes way back is Louis Pasteur who of course, was one of the early, the scientists of the world and said, "Chance favors the prepared mind.” So you know, it's this idea that you're not exactly sure how the future’s gonna play out. But if you build the right skills and flexibility, you're gonna be ready to take advantage of it. And then the last one, which is I think. We all have an obligation to channel our resources and energy to help drive impact with those people in need. And Muhammad Ali had a great quote that says, you know, “Service to others is the rent you pay for your room here on Earth.”
00:02:50 Scott Snyder
And I just feel like that's it's once again it brings it back to what things are all about, you know, in the end, yeah, making money is great, but it's also about channeling your abilities back into helping others.
00:03:03 Lisa Hochgraf
Wow, what a lineup of three quotes, two about learning, which of course CUES is a learning organization. So I love those. And then a third that's so germane to credit unions, which is about helping others, turning it around. So you can learn, learn something good and go help somebody with it.
00:03:18 Scott Snyder
For sure.
00:03:19 Lisa Hochgraf
Fantastic. Scott, back in 2019, seems like forever ago, but really isn't quite that long ago, you published a book called Goliath Revenge: How Established Companies Turned the Table on Digital Disruptors. Would you tell us about some of the main ideas in that book that might apply to credit unions and fintechs?
00:03:39 Scott Snyder
Yeah. And and kind of the genesis behind Goliath’s Revenge. I've had the good fortune of being in innovation roles in big companies like Lockheed and GE, but I've also been part of startups and founding startups and having been on both sides and then actually spending time in venture capital, I saw this like chasm between large companies and startups.
00:04:02 Scott Snyder
And I couldn't understand why large companies have these amazing advantages they're gifted with and it's not even just large companies, it's companies that are established that have been around a while. You know, they have things like brand equity and industry knowledge and expertise and data that they sit on that startups would kill to have.
00:04:23 Scott Snyder
And yet they can't get out of their own way sometimes. They can't run at the speed of a startup or the speed of digital. And we started studying this, me and my co-author Todd Owen, and said, why doesn't this happen and are there big companies that are able to harness that kind of entrepreneurship, that startup-type speed with all the resources of a big company or or a Goliath. And so that's really what the book is about.
00:04:48 Scott Snyder
And really we focus on six rules.
00:04:50 Scott Snyder
The first is if you want to be a disruptor, you can't think of 1X. You can't think a little bit better than last year. You got to think 10X, a real step change in value for your customers or market and if it's really 10X, you're not gonna get there tomorrow. You have to have a staircase approach to get there overtime.
00:05:07 Scott Snyder
No. 2 is to bring your whole company along. You need to balance little i and big I innovation. Little i is that incremental continuous innovation that's really the lifeblood of the company that makes your product, services and experiences better each day. And your employees are most equipped to deliver that little i innovation. And yet in most companies, we make it so hard for the average employee to bring a new idea or innovation to impact or scale.
00:05:34 Scott Snyder
There's just too many things in the way, right? Or not enough time, not enough budget. So how do we grease the skids so that those innovations from the front lines can truly scale and become impactful for the company? And then we need to balance that with big I, which of those disruptive bets that we have to make on what the future version of ourselves could be, and that might be very different in terms of how we make money, what our business model is, how we operate. And those changes are significant enough that we can't do that just within the core business. We need to create space and air cover for those big I innovations to run really fast and test and learn and fail and succeed. But it's important we do that because the world is going to change, and we need to have those bets ready to pay off, and they need to have access to all the core assets of the company to really succeed and and scale.
00:06:28 Scott Snyder
Third is, and this is very relevant to today's conversation, is using data as currency.
00:06:32 Scott Snyder
I think every company is a data company. They just don't realize it yet, and they're sitting on amazing sets of data assets, but sometimes they don't know. I like to call it the data balance sheet, just like a financial balance sheet. What is your data balance sheet as a company? What are those data assets and how easy is it for innovators or partners to get to those assets?
00:06:54 Scott Snyder
Because if you can do it and turn that data into currency, it becomes a huge advantage for the company in terms of attracting innovation and customers and personalizing experiences, et cetera.
00:07:07 Scott Snyder
And No. 4 is also kind of a mindset shift.
00:07:08 Scott Snyder
How do we think of our company as a platform that we could open up to innovators outside our walls and really use innovation networks to power our growth versus trying to do everything ourselves, and credit unions are pretty good at this because they recognize they need to almost cooperate to really drive innovation. But if you can do that
00:07:28 Scott Snyder
on a systematic basis and a repeatable basis like P&G has done in the past or other platforms that are really good at kind of opening up their ideas. NASA did this, and that was the example given the book. It's like multiplying your R&D department because there's all these innovators outside: startups, individuals, tech companies
tech companies that would love to work with your expertise and data, but we make it really hard in most companies to do that because we want to control everything. No. 5 is valuing talent over technology and as much as I'm a technologist at heart, I also recognize it's all about people, not just the typical hard skills digital talent.
00:08:08 Scott Snyder
I call them the 3 Ds: design development data science.
00:08:10 Scott Snyder
But it's also about how do we rethink every role in our company and organization in a digital-first or AI-first world. So what does an HR analyst look like in a world that we need people that can take data and understand when the next employee should get promoted or what kind of person we should hire next in a given role?
00:08:30 Scott Snyder
Or we might need somebody in our procurement department that knows how we can spot vendor risks sooner using analytics and AI.
00:08:39 Scott Snyder
But all those roles are going to morph and emerging tech and tools like AI are going to become embedded in those roles. So how do we help employees understand that and then give them a pathway to get there with training, mentoring, micro experiences, all that? And then how do we make sure our leaders are equipped to go drive that change and be what I like to call triathletes
00:09:00 Scott Snyder
where they can look ahead, execute today, but also innovate for the future. And then the last one which is very relevant to credit unions because I think credit unions live this pretty well as reframe your purpose.
00:09:12 Scott Snyder
So is your purpose relevant to the next generation of digital customers, innovators and partners that might want to work for you? Do they get it? Do they understand what you stand for and how you're going to drive impact just beyond making money? And I think that's more important than ever. If you're going to drive these other initiatives. So anyway. Those are the six rules in Goliath’s Revenge, and we talked about examples of every one, but they certainly apply in the credit union and financial service space just as much as anywhere.
00:09:44 Lisa Hochgraf
What a great list all from Goliath’s Revenge written in 2019. So knowing publishing a little bit that was actually written maybe in 2018 before it got published in 2019, and now we're on the verge of 2024. Actually, as this is publishing, it is 2024. Would you update this in any way? Are there any special considerations you would add to that list and the summaries?
00:10:07 Scott Snyder
Well, first of all, you know how with any business or leadership book, you just hope you pick examples or cases that have longevity, and we were pretty fortunate we did. The companies we picked weren't just fly by night stories. All of them are on the journey and none of them have gotten it perfect. But I think they represent good examples, companies like MasterCard and GM and like I mentioned, NASA and Discovery Health.
00:10:30 Scott Snyder
But I think you know in terms of the rules, the rules are really enduring, because I think they're just as valuable, maybe even more important today. In fact, I still have executives from global 1000 companies that call me up and say I read Goliath’s Revenge and like, this is exactly what my team needs. And these are within the last year so the rules are still sticking.
00:10:53 Lisa Hochgraf
That's pretty cool. Nice work.
00:10:53
Yeah.
00:10:55 Lisa Hochgraf
I read as I was preparing for the show that you have a lot of experience with both managing emerging technologies and with strategic planning. What advice do you have for top leaders at credit unions like board members, CEOs, CIOs for how to think about emerging and potentially disruptive tech and include this as they do their strategic planning?
00:11:16 Lisa Hochgraf
Big question, sorry.
00:11:17 Scott Snyder
Yeah. No, it's a great question. And the biggest fear of any leader, and I'll throw boards into that as well, is being on either side, either investing too early and too much or being too late and being caught flat-footed and and, you know, getting left behind. So, there's a tool in the technology world called the Gartner hype cycle that you may have heard of, and it starts with this. You know, it has this funny looking giant hump right at the beginning. It starts with the technology trigger. Then it kind of quickly ramps up to what we call the peak of inflated expectations.
00:11:54 Scott Snyder
Then it drops quickly down to the through of disillusionment. And then there's the slope of enlightenment, and eventually there's really this notion of it becomes mainstream or not, right. And typically, every emerging technology goes through some shape or form of that, right, where whether it's blockchain, whether it's metaverse, whether it's even going back to the Internet right in the early days. People see this amazing thing, and they start thinking about the promise and the capabilities. But then there's this reckoning of how does it actually drive impact in an organization with a whole bunch of humans and organizational dynamics and customers that have certain behaviors?
00:12:34 Scott Snyder
And sometimes that takes a long time to realize that impact, and I would argue with things like blockchain and metaverse, their technologies that eventually will drive value. They have some inherent characteristics that are really cool and unique and and can be used for powerful things.
00:12:51 Scott Snyder
But it may take a while for the players and industry to really understand how to organize.
00:12:58 Scott Snyder
So sometimes technology is way ahead of an organization's ability to absorb it, and I think we run that same risk with generative AI. Right now, it's an amazing technology, maybe more than any other emerging tech. The capabilities are visible to the average person, but you don't have to be a data scientist to here into the black box and understand.
00:13:18 Scott Snyder
This is AI. It's, you know, it's basically go generate a cool image of me on a Ducati motorcycle or show me a variant of my promotional brochure for a young demographic. I can generate that instantly. I don't have to go into a studio or hire a bunch of creative people.
00:13:35 Scott Snyder
So that's powerful, but the question is then, how do we get it through all the normal machinery of doing business—the regulatory reviews, the consumer panels, the feedback right—and make sure it's consistent with everything we do. So we just have to be careful. A) understand these cycles happen, and there may be these rare technologies like generative AI that maybe they skip over the through of disillusionment and they go right to mainstream adoption and it could be we're seeing some of that uptake already.
00:14:08 Scott Snyder
But I think we just have to be cautious. So back to the question, I recommend two approaches. One is bottoms up, rapid experimentation. Let certain populations in your company actually play with this technology across different parts of your company. So they could see what's possible and actually see can it drive the impact we think right even on these low-hanging fruit use cases obviously with some guardrails around it. So we don't get in trouble and then we should work future-back, using things like scenarios of how this could play out. How could it fundamentally change the way we operate or make money? Because that will get us thinking about what's possible in the long term and the bottoms up and top down will hopefully get us to a point as the future plays out, the ability to adapt and flex as we need to.
00:14:58 Scott Snyder
So I don't know, that's a long answer, but bottom line is yeah, you need to do bottoms up, rapid experimentation. You can't just sit around and wait. You've got to play with these technologies, but also you need to think future-back of what they could really do to your organization to think of those “big I” innovation opportunities.
00:15:17 Lisa Hochgraf
Thank you for that. Yeah. My next question also has to do with sort of what do we do right now and how do we think about the longer-term future. You recently presented a CUES Virtual classroom called “Leading in an AI-First Future.” And in that session, you presented ideas on how to balance these near-term value opportunities and longer-term innovation possibilities.
00:15:39 Lisa Hochgraf
For AI, can you say a little bit more about how credit unions can balance those two for fintech more broadly?
00:15:47 Scott Snyder
Yeah. And I think I think credit unions are inherently wired this way, but it's something I reinforce to every company I've talked to and it's not just about AI or any, it's really for any emerging technology but AI especially because of how powerful and also how volatile it can be is you have to start with responsible innovation.
00:16:07 Scott Snyder
And you've got to have your own responsible innovation framework that includes things like ethics and transparency and fairness.
00:16:14 Scott Snyder
All the things you stand for in your own values, but translated into what you want your solutions to do or not do, and that needs to be clear to everybody in the company, not just a few people in the tech group. So I would, if you don't have one, say, here's our responsible development framework for AI. Make sure it's clear to people across your company, because then that provides the backdrop of like, what do we really care about when we're innovating these solutions and make sure there's clear areas we don't.
00:16:44 Scott Snyder
I go #2 is I'm a big fan of simplicity, so I always talk about 3 Rs when you pick use cases you wanna go after because there are some use cases that just aren't ready like because the technology is too immature and the last thing you'd want to do is deploy, say a gen AI customer service agent.
00:17:04 Scott Snyder
To your customers, that's spewing out nonsense, right? Or hallucinating because you know, especially in a regulated environment that could result in some not good things either harming a customer or getting in trouble. So really you need to think about what use cases makes sense for us to move on now where there's you know real impact, but we can also manage the risk. I start with three R's. The first R is responsibility, so that goes back to the responsible development framework and it meets our guidelines and frameworks of how we want to develop these things do no harm, you know, and all the other things, ethics, transparency, fairness.
00:17:42 Scott Snyder
Is can we live with the reliability? That's the second R is reliability given the use case. So if the use case is, it's somebody in marketing and they want to generate the new ideas for a marketing campaign.
00:17:55 Scott Snyder
And maybe the risk of hallucinatoin or false positives or error is very low, right? So I get some ideas. OK, the woman in one picture has three legs, not two, but at least it gave me an idea of what I could do. So it's a brainstorming tool. But now, if I'm saying, let's develop a sidekick for one of my customer service agents that has to respond real time to a customer, and the risk that they might pass on what the AI says onto that customer could be high. Maybe I can't live with less than a 99% reliability or allow more time for a human review in the loop, right?
00:18:32 Scott Snyder
So the reliability is important and then the third R is ROI. Like it's it's great to chase all these things, but I think I see a lot of people spinning up a lot of pilots around AI, but not a lot of them are asking the question early enough. Will this drive real business impact? And it's not just about yeah, can we build a POC (proof of concept) that shows that we can save 10 hours on this given task but what if we have to add more reviewers later in the workflow to, you know, make up for the fact this is coming from an AI? Or the fact that maybe to stand this up it's gonna cost a lot of money because we gotta run our new servers?
00:19:11 Scott Snyder
So really thinking about the whole ROI of these cases, because they're not just pilots or they're not just basic proof of concepts, they're going to become products that somebody has to own and somebody has to, you know, continue to optimize and improve over time. So think of the life cycle ROI of these things. So I think if you start to think about those that will guide you towards what use cases really make sense for us to invest in.
00:19:39 Lisa Hochgraf
Yeah, it's really great. I like what you're saying about so much potential, so much opportunity, so many possible applications. And yet sometimes it still spews nonsense. So you have to account for such a simple but very big problem.
00:19:54 Lisa Hochgraf
The pre-reading assignment for that virtual classroom course you taught was super interesting. It's an article from Knowledge at Wharton called The Looming Algorithmic Divide, and it gets into the idea that AI in particular doesn't reach all people equally. And that's a problem for companies.
00:20:12 Lisa Hochgraf
Is that a broader problem for fintech in general and and what are you seeing in this area?
00:20:18 Scott Snyder
Yeah. I think ultimately, if we play it the right way, it could actually bridge the divide. There's, you know, let's face it in financial services, not everybody can afford a world-class financial advisor, right? So imagine if in theory, we could take a world-class financial advisor and package them up into an AI, a sidekick that could help us with our own financial management decisions.
00:20:41 Scott Snyder
I think that's very possible someday, as long as it has the right checks and balances and it's got oversight. But that's pretty exciting, right? Or even having a less experienced advisor that could be paired with the AI to give me much more personalized service and to be able to really understand and go deep into my life versus just be transactional. I think we're starting to see that. You know, I spend a lot of time in healthcare, and I always think healthcare and financial services are like kind of like cousins.
00:21:14 Scott Snyder
They're both regulated. They both focus on trying to drive short-term behaviors that help you towards a long-term goal, right? Whether it's improving your health overall or whether it's saving for some big event in your life, there was just a study recently done using generative AI where patients put posts about their health condition.
00:21:34 Scott Snyder
And then they had human doctors weigh in on the post with comments and responses, and then had generated AI do the same thing and blindly had patients then rate the post from AI versus the humans and believe it or not, this was a Journal of American Medicine article, AI got rated higher not just in credibility of the answers, but also the empathy. The answers were longer and more thoughtful than what the doctors provided. Now once again, you know, would I hang my hat on small sample set like that? No. But it gives you a glimpse into what's possible. And once again, the average person isn't getting the expert right, whether it's in health care, financial services, other areas. So I think on one end I'm very optimistic that AI could actually improve equity for services and a lot of different industries but at the same time, if you're not careful about what data it's trained for.
00:22:31 Scott Snyder
For putting these safeguards in place to make sure AI is not weighing in on something it wasn't trained for, or even hallucinating, and a customer doesn't know that, or you don't put detectors in to tell a customer transparently, hey, this was generated by AI versus human, then I think we're going to potentially run into some risks for sure.
00:22:51 Lisa Hochgraf
So I like what you're saying. There's some sort of guardrails that credit unions could put in place as they start to implement this technology, especially when it becomes member-facing for credit unions. Are there any other sort of guideposts you would want to name at this point in the conversation?
00:23:07 Scott Snyder
Yeah. Well, I think it kind of goes back to having that responsible framework. I think industry has a window right now to take charge in different industries and kind of self-police ahead of the government because once the government decides they're going to be the ones regulating it, usually it's going to go further than we want, right and I think we're sitting on the precipice right now of a whole bunch of AI legislation, so probably the most.
00:23:34 Scott Snyder
You know, we've seen the executive order which only theory applies to government run systems, but it really does start to stretch into lots of others, right? The European Union AI Act is probably the biggest step up right where not only do you have to be able to explain your algorithms, but you need to be able to point to what source data it was trained on.
00:23:58 Scott Snyder
And when you think about large language models which are trained on broad sets of data, in many case public data, that becomes really hard, right? But that's the kind of if the industry can get ahead of that and say, hey, we can provide transparency, we can show users what source data this model is referencing or why it render to certain decision and make it explainable and not, you know, I always like to say, if we can make AI more of a glass box than a black box, then it, you know it has a better chance of being accepted by society versus not trusted.
00:24:30 Lisa Hochgraf
And you said something interesting to me too, in that answer all about what Europe is doing might be something to follow. Maybe there's sources we can look at that might be a little bit ahead of where the most of us are. Are there some additional ones besides that act in Europe that you would call out?
00:24:46 Scott Snyder
Yeah, I think just like we saw with privacy laws and GDPR, I expect Europe to be the leading edge. They've always been a little bit more progressive on privacy and protecting individual identity and rights and data rights. So I think that's now translating into the AI world what innovators in Europe are worried about is that may put them behind on the innovation side, relative to the U.S. You know the U.S. is definitely ahead on generative AI in terms of most of the big companies are coming out of here with the exception of a few in Europe and a few in China so I think there's going to be some kind of balance. I would expect Europe to be the leading edge, just like in privacy.
00:25:26 Scott Snyder
You start to see a lot of the progressive states in the U.S. really moving to a GDPR level type privacy law, whether it's the California State law or New York Shields or others. And I think the same thing's gonna happen at AI. There's quite a few people in Congress that want that level of accountability and transparency.
00:25:45 Lisa Hochgraf
I also like what you said about this as a real opportunity for industry to get busy leading the way so that government doesn't get too far.
00:25:53 Scott Snyder
Yeah, I think I think government saying and listen, you know I have a lot of friends in government. It's so hard for them to have the level of expertise that industry has to even be able to understand how to you know, what is a certain type of algorithm and how do we when we train it, you know make sure the source data is referenceable.
00:26:13 Scott Snyder
Like, those are things that you can say, but to actually do it as the data scientists or the AI engineers much harder so.
00:26:20 Scott Snyder
So I think having industry educate the government is actually a really good thing right now. And I think there are companies, open AI and others are trying to do that. But I think if we do that by sector because in the financial service sector, we have our own set of regulators, right? How do we how do we help educate them and align with them on what's going to protect, most importantly, protect customers and then second, you know, make sure companies can really take advantage of this innovation in a responsible way.
00:26:51 Lisa Hochgraf
Scott, you've been really generous with your time, and I appreciate it. Before we wrap up the show, is there a question that I haven't asked you that you would like to answer for our listeners?
00:27:02 Scott Snyder
You know, the big thing that excites me about financial services and a lot of people are like, oh, financial services, is this, you know, old traditional industry. I kind of think of financial services as oxygen, right? I mean, next to social media, it's probably the thing we touch the most in our life on a daily basis.
00:27:20 Scott Snyder
And yet I think we consistently undershoot the level of experiences that customers expect, right. And I think that presents an opportunity I think for our companies to really say as we look at these emerging technologies, what they're capable of, if we can channel that in a responsible and protective way with the customer in mind and really do it in a way that we build trust.
00:27:44 Scott Snyder
It could be a huge advantage and I think I don't know how much you know about DBS Bank. I think they're one of the most innovative financial service companies in the world. They're based out of Asia.
00:27:53 Scott Snyder
Their purpose is to make banking joyful and really, if you look at the way they innovate, they really believe that, right? They believe that banking should be something that makes people happy, that fits into their everyday lives, that's integrated and embedded with the things they like to do and not a chore or an obligation or a road block. I think these technologies give us some amazing capabilities to get there, but I think it's all about stepping into the expectation that our customers have and delivering on that or over delivering on it. So that's what's exciting about right now and giving them kind of superpowers to pursue their dreams and get achieve the goals they want financially.
00:28:38 Lisa Hochgraf
Wow. Financial services as oxygen and as something joyful. Now, thank you for the closing inspiration, Scott. Really appreciate you being on the show.
00:28:47 Scott Snyder
Thanks Lisa.
00:28:49 Lisa Hochgraf
I would like to thank you, our listeners, for taking time out of your busy schedules to listen to today's episode of the CUES Podcast. And many thanks to Scott for sharing so many insights about leading during these technologically “interesting” times. If you liked the show, you could learn more about how to address fintech innovations and challenges by attending CEO Institute: Fintech. Find the syllabus and register at cues.org/fintech.
00:29:16 Lisa Hochgraf
Find a full transcript of this episode at cumanagement.com/podcast159. You can also find more great credit union-specific content at CUmanagement.com.
00:29:30 Lisa Hochgraf
Thanks again for listening today.
CUES is an international credit union association that champions and delivers effective talent development solutions for executive staff and board to drive organizational success.