Entrepreneurship Podcast post

Utilizing 1st Party Data with Rich Edwards

George Grombacher September 14, 2023

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Utilizing 1st Party Data with Rich Edwards

LifeBlood: We talked about how to tap into 1st party data, what 1st party data is, using AI and machine learning to better serve customers, threading the needle between compliance and productivity, and how to get started, with Rich Edwards, CEO of Mindspan Systems.      

Listen to learn how to use 1st party data to gain a competitive advantage!

You can learn more about Rich at MindspanInc.com , and LinkedIn.

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Our Guests

George Grombacher

Rich Edwards

Rich Edwards

Episode Transcript

george grombacher 0:02
Rich Edwards is the CEO of mind span systems, their company helping community financial institutions. With data. He is a artificial intelligence and data veteran having worked on and launched IBM Watson. Rich, excited to have you on. Welcome.

Rich Edwards 0:23
Thanks. Sure. It’s glad to be here. Thanks for having me.

george grombacher 0:25
Yeah, excited to have you on, tell us a little bit your personal lives more about your work? Why you do what you do?

Rich Edwards 0:32
Sure, yeah. I’m kind of like an unlikely entrepreneur to be in this position. My, my background from from a career standpoint is I actually started in the military, I was an Army officer. This was in the 90s, it was a completely different deal. And I actually left the military in 99. So before all of that changed radically. I ended up working in operations for a while, went back to school for a little bit. And then finally ended up at IBM, and work largely in what would be considered, like infrastructure type jobs. So this is datacenter automation, it was largely working in software, and ended up working in the finance industry supporting a lot of like, very large banks, institutional banks, if you think Wall Street think things that are like Social Security Administration, Federal Reserve, but worldwide, spent a lot of times working with those clients, largely on what their requirements are, like talking about what type of problems you’re solving, and this kind of gets into post great recession. So Sarbanes Oxley. gramm leach Bliley act, some of the things from a data retention and handling standpoint, like the job of finance changed, and one of my jobs was kind of help them from a technology standpoint, how do we address their needs, plus this like unprecedented consolidation, right? Hundreds of institutions becoming dozens on the very large side. And about that time, this was like 2013. So this is about 10 years ago, I got tapped to be part of what would become a whole new business unit in IBM, which turned out to be IBM Watson, it was the artificial intelligence. And, until that point, there and obviously in the PR type stuff, particularly like the the Jeopardy challenge, which had been driven by IBM Research, which is a whole weird animal, in and of itself, because it’s a lot more like university than it is like a Corporate Research and Development Organization. And there had also been a very long going knowledge management project that had been going with certain medical institutions, where they were doing research around practices within medicine that had a lot of innovation in them. And it was the ability of physicians to ingest that information quickly. So like reports and clinical trials and things like that. And they were beginning to use some of the same natural language understanding capabilities, and resources that IBM Research was creating, and applying it to that field. And that was like one of the first things that kind of got branded lots. And so I got brought in largely because they wanted to have a brand new offering that was developer focused, that was essentially a platform that our customers could build on top of. And that kind of sounds like a route thing right now, because every cloud service provider doesn’t. But at the time, really, the only thing that he saw there that kind of looked or smelled like developer services for AI was was largely telephony. The big player there was was with Android investments. So there’s a lot of like text to speech speech, sec stuff that was in like a phone context, right? That that was how they’re using it. But there wasn’t a lot of other things around that from natural language, understanding natural language processing. And we had a lot of really interesting cool things that a lot of it at that time was the proverbial hammer looking for a nail. It was like a lot of neat stuff, but it wasn’t really obvious how it would get us. So our job beyond building the product was kind of taking it out on the road and taking it to a lot of different customers and say, Hey, here’s like, two dozen things that you can do today that you couldn’t do before, or would take a very long time, but we’re very labor intensive, particularly from like, for processing and understanding large amounts of unstructured text or unstructured data, which you kind of think of like text, video audio. This is stuff If that isn’t in the spreadsheet, right, it’s not tables and rows, and the ability to process that and understand it and go, What is this about? What is it? What is what do I get out of it? What do I understand that it means? And particularly if it’s written by a human? What is the sentiment? Like if they’re talking about a subject? Is it positive, is it negative, right? And it’s the combination of like three or four things that were kind of well understood. But it was being able to do it very quickly at scale. And in this consumable fashion at the time, we were just doing it as essentially, as API’s, right things that you can incorporate into their products. And that was a fairly novel idea. Again, we’re talking 10 years ago. And so that was that was really great, was really interesting. And me being the guy that I worked with all the large banks and kind of talk bank, I was the bank guy for Watson for a while. And so I did the roadshow at all different banks and walked around and did that for several years. And it was it was very interesting. It was drinking from the firehose and trying to combine this kind of very technical, you know, deep understanding of this, like new cutting edge piece of what we were doing in the domain of finance. And that’s, that’s what I did. And that went for a while. And we can talk about this if you want, if anybody has questions, I’m happy to talk about it. But I kind of think IBM missed the boat on this from from a strategy standpoint, and you know, way more interested in being an enterprise services company, then they weren’t necessarily being a product company. And about that time about 2018, said, this maybe isn’t for me in the long term and time to move on. And I went out and I was, what I was really looking for was was this idea that I thought was coming, right, this kind of combination between what machine learning what artificial intelligence could do with the promise was, and in particularly in domains where, frankly, data was really valuable, and you’re largely looking at like regulated industries at this point. So the two biggest ones are healthcare and finance. Were particularly banking, in particular, I was kind of looking for a company that had expertise in that, particularly the ability to go and serve those those companies, but also had the potential to begin to add, you know, and absorb this new technology and help their customers. And that’s what eventually led me to mind span. Because they had a very long track record, both in in financial services and banking. And on the healthcare side, we’re working with several companies that, you know, they were able had the skills and capabilities to like work under the alphabet soup of regulation for finance, but then also healthcare under things like like HIPAA regulation, you know, handling patient data. So that’s kind of what got me to where I am today.

george grombacher 8:00
Nice. So you literally have this supercomputer that can do things that we’ve maybe never even imagined, and you’re going to these big banks, and you’re saying, you’re saying what we can do this? Or is it? What would you like to be able to do? If you could do anything? How does that conversation go?

Rich Edwards 8:25
It usually starts with a very specific pain point. A lot of times when we talk to customers, they’re dealing with something that maybe isn’t directly related to technology at all. Right? It’s it’s a competitive standpoint. It’s sometimes it’s a compliance issue. And one of the one of the things that, you know, is an underpinning idea of what we do, it’s a core idea is, first party data is valuable. When I say first party data, what I mean is the data that companies and organizations have, about their markets, their customers, how they operate, things that are unique to them, even if they have many competitors, even if they have many larger competitors. There’s an awful lot of things that they know that is not public information. And that’s generally classified. There’s some more nuance to it, but that’s generally classified as first party data. For most regulated industries. first party data is seen as a liability. It’s this thing that has like this compliance noose around and they are generally have the posture of for data needs to be protected. And when we think about data governance are how we handle data. It’s very much from a compliance and a protection standpoint, which they absolutely have to do because there’s a whole lot of stick from a regulatory oversight. employees to make them do that. What they don’t have is a really good idea of how can we make our products and services better? How could we be a more competitive offering in the market if we weren’t able to use this data completely in a compliant way, but in a way that helps us serve our customer better, to be more personalized to be more relevant to them. And that’s usually where they the gap is. And a lot of the initial conversations is just kind of talking about this sometimes uncomfortable tension between use hammer, let’s make that I don’t comply. And why this is kind of more of an issue now was right around 2019. This was kind of just before, just before the pandemic, and it really got accelerated in 2020 2021 was the interest in like the direct to consumer whole segment in financial technology is the more p2p payments like Venmo, which is part of PayPal, or cash app, which is actually part of square what’s now called Block. Also things like there’s a company called Sofi, which is kind of famous for doing Student Loan Refinancing. They are of the size now that they sponsor the stadium that the LA Rams you know, like they hit Super Bowl there, right. So also the charges are the same stadium, but But it’s so far stadium, right? They are like that they are now like a household name. from a brand standpoint, well, they all play in this space of financial technology that in some way, augments and helps traditional banking and in other ways, it’s in direct competition. And so what you saw was it was a, it was a banking industry, particularly at the Community Banking level, a small local bank, suddenly found themselves competing with companies that they had never heard of, they had never had to compete with before, largely, you know, these kind of like tech driven venture backed companies. And in that time period, like 2021, through actually like the end of 22 was this massive acceleration of investment that went into FinTech worldwide, but in the US in particular. And they you saw a lot of lot of these, like smaller financial organizations begin to be overwhelmed with the competition they were facing for like, not comprehensive across the board banking services, but for like, very well hold. Very high touch high design, very well done customer experience for like point products, right. Payments was one of the big ones. I remember seeing analysis from I think it was Park investment, that they had looked at how long it took both Venmo and cash app to get the same number of accounts, not dollars, but the same number of individual accounts, as JP Morgan Chase had, who’s the largest, the largest retail bank in the world. And you saw JPMorgan Chase largely did it through acquisitions that started about 1990 Up until this year. With with Republic bank, and you know, several billion dollars of of m&a is exercise, I think, yeah, several billion dollars of m&a. Maybe it doesn’t like big bank mergers. And you saw Venmo to it, I think in about seven years. And Cash App who started several years later, they only did it in five. And they were both in this like exponential growth in their acquisition of customers. And it just kind of showed like how business was done how growth work in consumer financial services, as the game has completely changed. And so that’s where a lot of smaller community, financial banks and credit unions find themselves today. And that’s really the marketplace where we work to kind of help them remain relevant. And frankly, be able to use that first party data they have better to serve their customers better.

george grombacher 14:41
What are some what are some use cases that some of these community banks have have implemented that is helping them to be more competitive?

Rich Edwards 14:52
Yeah, a lot of them kind of fall under the big tent of personalization And when I say personalization, what I mean is there’s both the element of you kind of think of things like personalized communication, you get an email on hazard gain. Like that’s like real KNOCK KNOCK Lopes, that’s just blocking attack. This is more, I understand you either as part of a very, very small segment, not one that’s defined by where you live and how much money you make, and, you know, sex and age and things like that. But like from a behavioral Steve, right. And really, the idea there was trying to get down to a segment of one, that when I interact with you, or you interact with me, whether in branch at the ATM, via partner via email, or thing I send you in the mail, or when you log into the app, or you do anything that’s kind of revolves closely around your financial lifestyle, I am talking to you as an individual. And what I’m presenting the problem as easily and as efficient as possible, and pointing you in the right direction. In a real simple version of this is, if you have a holistic view of your customers, right? You can help them and in ways that creates, you know, these kind of like really like wow moments, right? So real simple one. And this is like an easy one to do. It sounds cool. But it’s relatively easy to do. Somebody logs into your, into the bank’s website, and they begin searching through the knowledge base for fraud, how do I report fraud, fraud questions, FAQ and fraud. And then they pick up the phone and call, right? You have everything you know, right now to understand that this phone call is about fraud. Don’t put them through a phone tree. Or if you do make the first option fraud, or connect them directly to the fraud department, that this element of I know exactly what you need. And I’m here to help you to get it done. And I’m not going to make you lift a finger to do. Right. That’s, that’s that’s like that next level up of like, we are using your our data in a way to make our service better free. This is that much better. Understanding when you’re kind of hitting certain milestones in life when certain things are happening and being there proactively with advice, assistance offers for what’s going on. One of the one of the things right now that I see an awful lot is there’s there’s an idea of asset flight, right, that are kind of people are taking their money and trying to move to a safer, safer place, right, which largely means like very, very large, too big to fail banks. What you see community banks doing very well right now is that’s not happening to them. And it’s largely because they’re having these like one on one conversations with their customers, and able to treat them as individuals, particularly they come in and they say why I want to cash out the CD because I’m moving it because I get a half point. Better, right? They see less of that. But when they do see that they’re able to kind of step in and say, well, let’s let’s talk about why what you’re trying to do, here’s how we can help you how our offers are as good if not better, for what you’re looking at plus, let’s think about long term what’s going on, right? And like, just the ability to have that conversation. As you get bigger and you have a more industrialized at scale organization that runs more like a factory than it is a local community financial institution, those conversations have happened way less often. And they’re they’re more mechanical, and they’re less personal. And so their ability, and really what they’re trying to add here is if they can use that data, they have to make that level of service, that personal level of service that they’re so good at, in a branch that like hundreds of years, some of these institutions have been on, if they can make that available and inherent in all of their channels, all of their brand touch points. They’re almost unstop for a lot of what they’re doing. They like that is an unfair advantage they have against even the largest institutions.

george grombacher 19:17
That is very cool. Right there. So you sit down with a community bank and what is what is the implementation process typically, is there a typical process?

Rich Edwards 19:33
We start off with an AI trying to like talk about like, well, what are you trying to do and what’s the hard part? Because the technical lifting right there like we would love to do X, but we don’t have access or we do but it’s very slow, if we’re not able to do it in a timely manner. And, you know, for a lot of times, talking, building something, you know, a technical solution at this level, like, that’s not a thing that community financial institutions do, like they buy solutions, right? So anything that doesn’t come out of the box for them is it’s, there’s a gap there, like they’re not going to naturally have. And so a lot of times, it’s like, what’s the what’s the simplest version of this that we can do that we can help? How can we get the right information in the right place at the right time, and there’s a lot of ways to do. Like, that’s, that’s really not the hard part. And, you know, I don’t, it’s not like a failing on their part, because you think about the school the skills like technical architecture, and, you know, database design, you know, things that kind of get into the more implementation side, like this, the thing they’re going to do once every 10 years, right. So it’s not worth it for them to actually build this out, it’s, it’s worth it for them to kind of bring in advice, do it. And for a long time, there’s been like a half dozen vendors that that, that kind of do the core banking systems for a lot of these institutions. But they they’re at least a decade behind and what the requirements are. And because they have, it’s not quite a monopoly, it’s more like an oligopoly. There’s like three or four players, for them from a core banking standpoint that have like a 90%. Market share, really, the latest and greatest and do a lot of product development for them, because they have a great franchise that they can cut a harvest. And so they find themselves this like greater requirement, they need to be competitive. And the vendors and the core providers they’ve relied on for a long time aren’t terribly incentive to help them with this. So that’s kind of where that gap is, it’s, it’s, we know, we have to do more. But we can’t use the systems in the process, and really the people that we’ve worked with for decades to help us do that. So it shows like, the new and we’re going to do it and in May, and it’s not going to be part of this simple monolithic system that you do every in your bank around, like, we’re going to create a layer that recognizes number one, the value of the data that you have to let you take ownership of it, ownership of it, it tipping control, and everything kind of falls under that not just compliance. But how do we make sure the right data shows up in front of the right person at the right time. Like putting all of that on top of there with this understanding of this data is valuable, it’s only getting more valuable when you start to layer on things like what artificial intelligence and machine learning can do? Just a simple question, right? At some point, they’re going to have the ability and just frankly, everyone is going to have the ability to cheaply and efficiently create their own large language model their own chat GPP, right, where you can like ask these like very plain language questions or say, create a list of customers that do XY and Z for me. And in all of the things that would normally be like SQL coding, and, you know, database design, and how do we bring all this like, all of that gets abstracted away, you’re going to be able to do that on your own. That’s going to be available to everyone. But it’s only going to be valuable to you, if the the answers that are coming out of that are unique to you. They’re not something that has, you know, been sent off and given away to a third party vendor that has been, you know, just aggregated together in some central repository, then it’s great, it helps you, but it gives you no competitive advantage. So the understanding of like, what’s in there, that’s going to be really valuable, it’s valuable today, but it’s going to be much, much more valuable and really give you like, probably the core part of your competitive advantage going forward. Like that’s the part you need to get your hands on today. And be ready to like, how do we structure this and begin to put the practices in place, so that this is only like a compounding asset for us going from right, take it from a liability to address that discussion that like change in how they view things. That’s the hard part. That’s the part that actually takes the most technical implementations, the thing that kind of says, We can show you, you know, an impact of doing this in the next quarter, you know, that you can show the boss and make the CFO happy, right. That’s usually what we’re shooting for. Right? You want to have an impact that that it doesn’t matter what you’re doing or what’s underneath it, but you know, the risk officer is happy and CFO is happy, and that’s really all that matters. That means your budget gets to at least stay the same. If not go up next year. That’s, that’s what we’re shooting. That’s what a good outcome.

george grombacher 24:50
That makes a ton of sense. Got to thread that needle rich. Well, thank you so much for coming on working People learn more to and how can they how can they engage with mind span?

Rich Edwards 25:05
Sure. Anybody who wants to reach out has questions for me take a look at look at some of the things that we write. I’m most active on LinkedIn. I think we’ve given you a link to that. But I’m rich Edwards on LinkedIn. Also, you can check out my expand systems where it might expand inc.com

george grombacher 25:24
Excellent. Well, if you enjoyed as much as I did show Richard appreciation and share today’s show with a friend who also appreciates good ideas, go to mind span inc.com check out everything that they are working on there, you could find rich on LinkedIn. And I will put all of those in the notes of the show. Thanks again rich. Thanks, George. Till next time, remember, do your part but doing your best

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