5 Keys to a Successful Data-Driven Strategy in Banking

Jim Marous:
Hello, and welcome to another Banking Transformed Solutions podcast. I'm your host, Jim Marous, owner and CEO of the Digital Bank Report, and co-publisher of The Financial Brand. And as financial institutions are preparing to engage in a data-driven strategy, where do they begin? First, it's important to understand that data transformation is a marathon, not a sprint. Successful financial institutions must align themselves around five critical keys that will lead them through a holistic data-driven strategy roadmap. Our guests today in the Banking Transformed podcast are Jason White, chief information officer at Berkshire Bank, and Mark Leher, VP of data analytics for Segmint. We'll discuss the development and execution of a truly transformational data-driven business strategy for financial institutions.

Jim Marous:
So welcome to the show today Jason and Mark. First off, I want to welcome you both to the Banking Transformed Solutions podcast, where we discuss [inaudible 00:01:10] solutions that can assist financial institutions with their digital banking transformation journey. Before we begin, for those of the audience that are not familiar, who both of you are, could you tell us a little bit about your background and your current roles? Jason, you want to start?

Jason T. White:
Sure, absolutely. My current role at Berkshire Bank is chief information officer. I have a wide area of realms under me, everything ranging from infrastructure to my IT risk, enterprise project management, electronic banking, and digital platforms. That's where data comes in. That's where our digital transformation exists. And I've been with Berkshire for three years now. Prior to that, I was in the same role at Savings Institute Bank and Trust for 25 years. So I've about 30 years of banking experience coupled with technology.

Jim Marous:
And how big is Berkshire Bank?

Jason T. White:
Berkshire Bank is around $11 billion.

Jim Marous:
Okay. And Mark, do you want to talk a little bit about what your background is and your role at Segmint?

Mark Leher:
Yeah, absolutely. And thanks for having me today, Jim. So my name is Mark Leher. I'm the vice president of data and analytics here at Segmint. So my team is responsible for essentially bringing in all the data that we get from our financial institution partners and transforming that into the insights that we deliver back to them. So that includes an ETL team, it includes a team of taxonomists and library scientists who are actually the ones with eyes on the transactions every day, putting it into the taxonomy and adding the appropriate metadata, cleansing those transactions, and then our predictive analytics team. So we take all the insights that we develop from that cleansed data and run predictive models. All of that data then feeds into our either delivered back to clients as data or via our marketing automation solution.

Mark Leher:
I've been with Segmint for two years now, almost two years now. I joined about 18 months ago. Before that I ran a boutique taxonomy and metadata consulting firm for 18 years. We actually worked with and Segmint was a client of mine since the first day of Segmint. So I've worked with Segmint for 13 or 14 years, but I've been officially part of the team for two years when they acquired my company.

Jim Marous:
Great. For anybody who's been listening to this podcast regularly, they know my passion for data and analytics and application of data and analytics across an organization. Most of them are also familiar with the fact that I believe it's the foundation of a strong digital banking and digital transformation strategy, but more importantly, the fact that while the financial institution ecosystem overall has not done very badly at all on using data and analytics to take care of risk and fraud, we have really not even come close to reaching our potential as it relates to using data and analytics for better experiences, better decision making, and really driving an organization. And the key here is that even though we rate ourselves pretty low in digital and data maturity, we have to remember that there are solutions out there. And Segmint's a great example. We need to partner with solution providers to get us over that hump between being a laggard or a mainstream player in data and analytics and being a leader.

Jim Marous:
So today we're going to be discussing the five keys to success in building a data-driven digital banking strategy. So just as an introduction, these include the auditing and the providing of a broad access to data across the organization. Number two, establishing business goals that drive a strong data-driven strategy. Number three, organizing, enriching, and categorizing that data to make it more usable. Number four, the integration of data for strong decision making. And finally, and just as important as all the rest is the measurement results and measurement of how effective your data is. So, as I mentioned before, even thinking about a data-driven strategy, financial institutions need to understand how to access their raw data and what it all entails. Mark, can you speak a little bit to this process?

Mark Leher:
Yeah, absolutely. And I think that speaks to the first point about the audit. And like I said, I've been in the taxonomy and metadata space for 20 years working with bank data, but also working with clients who wanted to organize their internal documents and make them more searchable or retailers who wanted to make their product data more findable online. And the common thread, the first thing I always would tell people, you got to start with an audit of the content and the data that you have. And it sounds trivial, but I've had so many conversations with organizations that say, "Wow, we'd really love to use data. We think data is important, but we don't know where to start. We don't even know what we do with it." And actually looking at the data that you have inside your organization is a great place to start because you can understand what data assets do we have? What shape are they in? Where do they exist? Kind of some very trivial things, and that can help you understand and begin to drive the ideation process.

Mark Leher:
Well, what can we actually do with this data? Do we have the data assets that are needed to support the business goals that we might have? Or when we go have a conversation with business users, we're armed with understanding, oh, you want to do this? Well, I think that this piece of data would be really helpful, or we understand you'd like to segment your customers, our customers by the, as an example, by the interest rate of the loan they're paying, but we don't collect that data anywhere and we need to start collecting it. So doing that content audit of what data you have, what systems they live in, and probably down the road, where you would like that data to be consumed provides a really strong foundation for putting a strategy in place.

Jim Marous:
Now, Jason, at Berkshire, at any institution actually, a lot of organizations hold back from doing anything with their data because they're concerned about what their data looks like, how it's structured, where to find it. And as a result, this issue is bigger than a breadbox and it's huge. No matter how big your organization is, there's a lot of data, there's a lot of sources of data. Data is not easy to use, not easy to access. So when you started the process at Berkshire and you're trying to develop your own data-driven strategy, where did you begin and how did you parcel this whole big problem so that you could work with it?

Jason T. White:
So first I'd piggyback to what Mark was saying. We got to know our data, right? Where does it exist? Exactly what you said. Where are our sources? We documented our sources, instituted a robust ESP or middleware platform, documented that. So we knew where our sources were. Really important. Brought it into one place for a single source of truth. You need to have a strong data governance program, right? You need to govern that data. You need to secure the data. You need to validate integrity after bringing it all in one place. So what we did was part of our best plan, our best plan is our overall overarching corporate strategy. It's a transformation plan we put in place, took three years to put in place. We defined our goals, and then we mapped those goals back to measurable outputs.

Jason T. White:
So going back to those sources of truth, defining our corporate goals, mapping those lines of business goals to the corporate goals and then taking the technology we built with our integration layer, engagement platform and map those goals to those various channels and data points. Another thing to throw on here too is as we're moving into this digital world, fintechs play a big role. So make sure when we partner with fintechs, we're looking at do they have the right data we're looking for? Can we use that data and can we bring it into a single platform?

Jim Marous:
In this whole process though, a lot of organizations just get stumped at the beginning point because it is huge. Is this a place where third party providers can help provide guidance, but also can take data that may not look perfect. And if you find a strong third party provider, can they help you structure in such a way that at least can get you to the next step?

Jason T. White:
Oh, I'd say absolutely. And that's why we partnered with Segmint. The analytics that they perform and the output and KOIs are really the foundation to a lot of our digitized pillar, right? Our customer experience, our customer journeys, our marketing campaigns. That really is the foundation. So we don't have to go through and analyze that data. It's done for us. And we bring it into our warehouse and we utilize that data to take advantage of the different technologies we have in place to align to those goals.

Jim Marous:
So when you're working with Segmint or whoever you end up working with as far as the audience is concerned, we talk about the second step is really building a data-driven strategy. And that's a hot topic right now in financial services, but can you give me a little bit of a definition around what actually is a data-driven strategy and what it is at Berkshire?

Jason T. White:
Sure. As I said previously, we aligned our data-driven strategy. Our full foundation is based off of data and digital. So whether it's taking the goals that were established and aligning it with data for measurement, data for action, data for marketing, it's all defined within there, within those plans.

Jim Marous:
So when you're doing that, are you also looking at more than just an application towards maybe personalization or maybe a lending goal or something like this? Actually, did you look at trying to make it so the data then could be deployed across the entire organization for better decision making?

Jason T. White:
Absolutely. Absolutely. And again, that's where your different platforms come into play. From a technology perspective, the ESP platform or your integration platform is what helps with a lot of that and drives some of the AI behind of that as well as your engagement platform. Depending on the solution that you choose, those platforms can take that data and help make more aligned decision making, but easier decision making, like you said, and automate a lot of the processes for efficiencies on the back end. There's a lot that I can talk to when it comes to where our plan captures a lot of that.

Jim Marous:
Yeah.

Mark Leher:
I really like that. And why the audit is so important is when you think of a data-driven strategy, I think of it as it's using data to either make informed decision making, whether that's in marketing or business intelligence. And so there's all sorts of understanding the systems that you have within your institution or within your organization can kind of tell you where could this data add value?

Mark Leher:
So at Segmint, we provide an engagement platform or a marketing automation platform that consumes the data that we provide and clients can create marketing campaigns and deliver messaging on their website or on the open internet based on the KOIs, but we've decoupled the data cleansing that we do into a merchant payment cleansing solution so we can provide cleansed transaction data that maybe sits into it could be another marketing automation solution, or it could be in a data warehouse. And so now that data warehouse where you have all these transactions, we can do much more advanced reporting than before. So it all feeds back to what systems do you have and what are some of those business goals? And then we can have a conversation about where to deploy the data to make that a data-driven strategy.

Mark Leher:
The last thing I'd add, I think the great thing about a data-driven strategy is it gives you an opportunity... Jason and I dig in to date all the time and I work with people... I work with data every day. I'm not an expert. I have my intuitions or guesses about what might work, but with a data-driven strategy, if you're are capable and you do the measurement and the governance, then you can do a lot of fun testing and test those hypothesis and the data will tell you where you're right and where you're wrong. Some days you're smart, some days you're not, but you can always be adjusting if kind of data is woven into the fabric of decision making.

Jason T. White:
Absolutely. And then I'd add an additional on top of the decision making opportunities. What opportunities do we have at this point utilizing that data to better serve our customer, to give them what they need, not we think they need? Right?

Jim Marous:
So really given what you just said, when we try to align our data in different strategy around business goals, it doesn't have to be an overarching corporate business goal. It could be a marketing goal. It could be a credit acquisition customer goal. So you can actually break this down so that if a person really can't embrace the entire project at once, a financial institution or their third party provider can break these into smaller pieces that can move forward together. Correct?

Jason T. White:
Correct. Correct. In our case, like I said, we're doing a lot. It is a marathon. We are sprinting a little bit. We're going through as a bank, a full transformation. So we're kind of hitting it all at once, which is a big chunk and a lot to do, but you're absolutely right. You can piecemeal this and attack one segment at a time.

Jim Marous:
Well, that's interesting because I've been meeting with bankers quite a bit over the last two months. Probably met with 100 bankers face-to-face. And right now they're buried in the messiness of today. To reach beyond that is really hard, even though they know and they totally understand and agree that they've got to do more. So the ability, I mean, not every organization can be able to do what you're able to do, Jason, at Berkshire that you can't necessarily take on the entire thing at once, but you can break it up. And that way you can make great use cases that can get it so that you have an ROI and investment that can be made going forward. So the third key is around organizing, enriching, and categorizing raw data. Jason, how do we take your core data and make it actionable against business goals?

Jason T. White:
I mentioned a few different layers that we can use. So first layer we're looking at, and again, digital and data, they go hand in hand. So a lot I'll talk to digital self-service capabilities, but you need the data to do that. From a digital banking suite perspective, right? We talk about personalizing that customer experience, getting to know that customer better. Due to the events in the 18 months, being a community bank, a purpose-driven bank, our relationships are key. Our service is key. How do we bridge that gap? So when we're looking at new digital solutions, we want to personalize the experience, enhance those self-service capabilities, utilize the best digital marketing and campaigns we can and offer not just rewards, but meaningful rewards. By taking that data, we can then say, okay, tailor it to a customer, give them a meaningful experience.

Jason T. White:
Secondly is our engagement platform to take action on the data. We can drive workflows, automate to create efficiency. I talked a bit to our marketing technology stack. This is where we take our strategy when it comes to campaigns, drive them with data. We drive our journeys with data and tackle social media at the same time. And then our CRM is what's going to complete the C360 with all of this data, bringing it together to present those opportunities.

Jim Marous:
So in this process that you're going through right now, what has been the biggest challenge that you face, Jason?

Jason T. White:
I'd say starting with the foundation of where is our data? Right? The first question you ask is where is it? How do we access it? So that was the biggest struggle. Where is all this data? So going out there, analyzing our different data points, our different data sources, bringing that all together into a meaningful warehouse that's again, governed, secure, establishing a strong data governance program. That probably was the hardest part. That was the biggest hurdle to get over. Once you have the data and it's all in one place, you can then pull that, take the goals and make that data actionable.

Jim Marous:
So Mark, when you're working with customers and potential customers, we've talked about the auditing and having access to data, we've talked about business goals and driving a data-driven strategy, and we talked about organizing, enriching, and categorizing the data. And even though these are the foundational parts that actually make the data actionable and usable, and even though financial institutions, every financial institution knows the importance of data, what are the challenges you've seen in getting a potential client to say yes or to move forward? What holds them up?

Mark Leher:
I'd like to go back maybe a little bit to the cleansing and the organization step. I think that is an important one to build on what Jason said. And it sounds like Berkshire is doing that and Segmint helps... You actually have to look at the data. And so sometimes, maybe, Jim, this ties into your question, sometimes that can be overwhelming. Did we do the audit? Where's the core data? Man, these transactions are really messy. So that's where having a partner to help you, one, understand that we can accomplish this challenge of making the core data actionable from your account information and loans and lines and your customer file to the transaction data. We can take all that information and cleanse it for you and turn it into meaningful and actionable metadata.

Mark Leher:
We can help our customers because there's a lot of human effort that goes into actually looking at that data. Like I said, I've got a team of five library scientists who are every day looking at the data. Every client that Segmint works with is assigned a client success manager. So that's a team of 10 people who are also looking at the data and looking at the results of campaigns and measurements that our clients are running and having conversations on a daily basis with partners like Jason to understand what the business goals are and feed that back to the taxonomists so that as they're looking at the data, maybe we don't care about the dry cleaners, but this client really wants to run a campaign to try to win back the Venmo users and convert them to Zelle users. So let's make sure we're capturing all that data for them.

Mark Leher:
This is a really big task. And in my experience in the data space, that's often where people fall down is it's like, "Ugh, we should be using data, but this is so overwhelming. We don't don't know where to start." So Berkshire is really lucky to have someone like Jason who's leading at the high level of an internal initiative to really drive a data-driven culture. Some people we talk with, it is just the marketing department and they have a problem that they need to solve. And it might not be an institution who's yet bought in or has that data-driven culture. So that's something they have to overcome.

Mark Leher:
And to finally get back to your question, Jim, I think it comes down to like a use case or an ROI that people can grab onto. Back to what I said earlier, a lot of people I talk to say, "Ah, we should use data. We just don't know what we do with it." If you can dial in to what we want to do with it, and it's something that's interesting and tangible, then there's an appetite for making the investments into an application or make an investment into data. And Segmint can come in and cleaning the data is just, yeah, it's a huge task. That's a great thing to partner on. Selfishly, I'll say that, but I think it's true. You read tons of articles about data scientists and 80% of their time is spent looking at and cleansing the data. So if you can find a partner who can solve that problem for you turnkey, it's a big time saver and it's going to accelerate the time to ROI.

Jim Marous:
So Mark, okay, so I'm a bank.

Mark Leher:
Yep.

Jim Marous:
And I'm about to engage with you, but I'm having trouble getting my hands around saying, geez, where do we start to make it so we have some success stories early so we can get investment later? So can you go over maybe some use cases, some success stories that you've seen that if you were in my shoes as a banker and I'm looking to say give me three or four use cases that I can hang my hat on that say, it's going to have a 95 plus percent chance of success, certainly driving a positive ROI. What will you give? Give me some examples of use cases you've seen in the marketplace that are really working really well right now.

Mark Leher:
Yeah, where I really like to start and where we start with clients is we say, give us your data and we can run a competitive insight report for you. So we can show you we can take all the transactions that we see and classify your clients, provide you a set of your clients who are making competitive mortgage payments to other institutions, competitive auto loans, HELOCks, who's using, like I said, the different peer to peer systems who might be using competitive merchant processing accounts. So that's going to give you a... That's really an opportunity report that's telling you here's all the money every month that's flowing out of your organization. So that's a great baseline.

Mark Leher:
And that's often with our marketing automation solution where our clients will begin to create these always on campaigns because once we've segmented your client base and we know who's making the competitive mortgage payment to Wells Fargo, you can run a campaign always on targeting members of that, we call them key lifestyle indicator. That's essentially just metadata about the clients. You could have a key lifestyle indicator that says that you're making a mortgage payment to Wells Fargo or Bank of America, but you could have a key lifestyle indicator that says you're a golfer or you like Starbucks. So you can then run an automated campaign targeting those Wells Fargo mortgage holders, and if they like Starbucks, put a cup of coffee in the imagery to personalize it a little bit. But we see the success of those campaigns to be... I just can't share the specific numbers, but just heard from a client today where the email open rate on these campaigns for the people I identified was over 30% and they converted I'll say many millions of dollars of account balances that were previously at a competitor too within their institution.

Mark Leher:
So that's just one example. And the great thing to kind of go to the measurement is because we're monitoring transactions, we can see once someone's no longer paying, we can see in the loan file that someone who received a message to refinance that they actually opened a mortgage with the institution that we work with. So that's kind of the full cycle attribution. And that proves the ROI. That's a great place for the marketing team to say, hey, look at this. We ran a campaign and look, the people who saw this message or opened the email or clicked on the link, they converted. It actually worked. And the ROI numbers that we're seeing are pretty fantastic. Definitely pays for the solution.

Jim Marous:
This is a great example, Mark. And we talk about it often on the show is that there are so many opportunities for low hanging fruit. Opportunities to take data that's out there readily available. And I get frustrated and the consumer's getting frustrated because the consumer knows you have the ability to see what they're doing. I get frustrated because my personal finance institution doesn't realize or doesn't take notice of the fact that I take money out on a regular basis for my Acorns account, or that I wrote a check and had a direct deposit for a car loan that, geez, when it's four years old, you're pretty dog on sure if I bought cars over the last four years, every four years, I'm about to be in the market for a car and I even wrote a check as a down payment for a car, never heard back from my financial institution offer me an alternative. And when you do it, a test drive for a car, they do a credit bureau. Not one that impacts negatively your credit bureau, but basically just to make sure that you can afford what you're looking at.

Jim Marous:
And what's interesting is most institutions don't take advantage of these very simple key elements, as you've mentioned on all these scenarios. So Jason, from your perspective at Berkshire, what are some examples that you've seen of data being able to drive really quick, easy, what I'll call easy results?

Jason T. White:
Everything that Mark brought up, we've layered in to our own technology and our own marketing stack, right? So not only will everything that you even mentioned drive a campaign, a marketing campaign, it will also integrate through our other channels throughout the bank. And whether you walk into a branch or your online digital, the roadmap will, our roadmap will integrate all those sources together. So it's much more than a marketing campaign. It's you go into a branch, I see throughout pulling up for Jason White, my customer 360 that, hey, you did do X, Y, Z. You did go out for an auto loan. You did meet all these criteria that the data that comes in from Segmint, and here's the opportunities we can take advantage of. Now, whether that's presented out through a marketing banner or an online banking or mobile banking or pops up on a screen as an alert for a teller that you're visiting, or you call the call center or are moving to sales center, they can take advantage of all that data across all those channels, right?

Jason T. White:
We also take it a step further where we're looking at this data and we're saying, okay, how can we use it more? How can we use it better? And I mentioned customize or personalize that your online mobile experience so that you can say, hey, Jason's a golfer. We can totally tail this. We can segment those customers based on those key lifestyles and give them their experience that they're looking for that they fall into. Create a single pane of glass, I know I'm going outside of kind of that analysis realm, but data's everywhere.

Jason T. White:
So we want to pull that data altogether and present it to a customer in one single a pane of glass, an expert's product, complete our households. I mentioned offer meaningful rewards. How many times are rewards given to you and you'll never use them? But if you take that data, analyze it, look at those KOIs, now you can say, hey, I'm really going to reward you for being with us, for being a member of our digital and banking community. And I hit this before, give the customer what they need, not what we think they need, right?

Jim Marous:
And it's interesting, Jason, because it says the beginning of it that you then distribute this in site to your teams and the branches and elsewhere so that any point at which the customer may interact with the bank, they have this information as a 360 degree view that everybody else has. And this is key. I've mentioned this on a couple other podcasts. Remember that your branch staff right now feel that they can be outplaced in a nanosecond by your digital banking strategies. One way to make them feel comfortable and work on behalf of what you're trying to do from a digital banking perspective is to give them the tools to do what they are most comfortable doing, which is helping to customer a member.

Jim Marous:
So if you provide, as Jason mentioned, if you provide your branch teams with data that says, here's the events that are taking place, here's the opportunities we see in the marketplace, here's people that we believe are going to be in the marketplace for X, and you give them those tools, these people are trained by personality type to help them member or customer down that path. And as they do so, they'll realize they're very much a part of that digital transformation journey. That they're very much a part about the bank's digital future as opposed to potentially being outplaced.

Jim Marous:
And this is such an important component that if you... Anybody who listens will realize that I say quite often, you don't use data to build better reports. You do it to build better experiences. And this is part of that. And Jason, a great share from the standpoint of what you're doing with the data once you have it in your hands and once you see these opportunities. So that's key. So, Mark, from a standpoint of measuring success, you referenced it a little bit in your previous answer, how do your clients do best at measuring the success of their data initiatives?

Mark Leher:
Oh, I think, Jim, the clearest example for Segmint and the primary use case would be, again, within our marketing automation solution where you can actually see the impact of the campaigns you're running. Because again, as the data's flowing back in through Segmint, we know that if that campaign message influenced the accomplishment of a goal, like I said, opening up a refinance or purchasing a CD, the client received the campaign for that, we can actually attribute that product opening to the campaign or the influence. So that's, I would say kind of the A to B the shortest line of how people are measuring the impact of our data.

Mark Leher:
Beyond that, when you begin to think about like our merchant payment cleansing solutions or some of our predictive analytics, that's really good to have a conversation with the client. And that's where our client success managers come in to understand what's the business objective to cleansing the transaction? Is it improving your digital experience? Maybe if it's improving your online banking platform, then you'd want to measure, well, we're providing cleaner transaction data within that experience and we're going to measure how many calls are we getting about fraud? And I think we've all had the experience where you look at your bank account, it's like, well, I don't remember making a purchase there. What could that be? And you call the bank and they say, oh, that's a coffee shop. You made a purchase there, or that was a transaction. But that time on the phone that they had to spend answering that question for you, we can reduce that by making what we're presenting on the digital banking experience more clear.

Mark Leher:
So that's another example. It goes back to, I actually think audit that first key flows through to everything. It goes back to that audit and understanding of the business goals. Once you know what the business goals are, now you can know what to measure.

Jim Marous:
It's interesting you talk about the measurement, you talk about success factors. This is also why finance institutions are really prime to use third party providers because you've gone down these paths. You know what's worked, what hasn't worked. You can bring success stories to finance institutions to make it so that you really... The financial institutions gets to their destination faster, that they have the ability to avoid those pitfalls that many of us would have if we tried to build these strategies internally. And I know that when I was in the financial services industry as a user, I relied on these third party providers say get me over the hump. Tell me how to win in here. Because at the end of the day, I want to make sure that I win. I want to make sure I get budget.

Jim Marous:
And this is where the third party providers can really help because they've done it with dozens and dozens of financial institutions as opposed to just building a mindset on your own. Jason, from your perspective, if I'm a financial institution just starting to embark upon my data strategy and my data foundation, data analytics strategy, what is the one suggestion you'd give them that you say, you know what, no matter what you do, try to remember this because this is the key to not failing in this endeavor.

Jason T. White:
Have a strong corporate plan with goals defined and actionable, tangible, and measurable by each member of your line of business. That's key. Definition, strategy first because from there, the data, where to get it, who to partner with, that'll all come in play, right? So that we can roll all of our information up. I would also say when you talk, and I'm talking strategy, when I'm talking strategy, map those out for Berkshire, we have an IT business plan which captures and plans for and is planned for the foundation, the technical foundation. I think the platforms, the middleware layers, all that stuff. And then we have a digital transformation plan which will take all of these line of business calls and map them to digital perspectives and data, right? So that they're all pointed out in two separate plans underneath that roll up into our corporate plan. So very keen on strategy. I think we spent three months just defining strategy and data and how it rolls into those plans so that we can work with our partners and work with the foundation that we have built.

Jim Marous:
It's interesting we talk about it a lot of times that we say if you don't determine where your destination is, you'll never know if you met it and reached it. And just as importantly, you can't measure toward it because you have no point of reference. It's kind like the GPS of data that says I need to know where my destination is to be able to get through the quickest and easiest. So finally, Mark, from the standpoint of financial institutions that want to look for a partner to get them across their data and analytic transformation journey, how does Segmint help?

Mark Leher:
I think we really help in two key ways. One is we simply have a world class data cleansing and enrichment solution. We've been doing this for 13 years. We have a knowledge base of 160 million plus in growing transaction strings mapped into a very detailed taxonomy that's providing actionable metadata. Got a team of, like I said, five library scientists looking at that data on a daily basis and a separate team of data engineers who are taking the output of the metadata and looking at the fields within the data, the raw data, and coming up with interesting new statistical calculations that might inform, provide more actual metadata, not transaction based, but people who have less than 10% left of principle and their mortgage loan.

Mark Leher:
That might be an opportunity. They're going to have some free cashflow coming up. We should get our investment team in front of them or whatever it might be. So that's one is we're just outstanding world leaders in data cleansing and classification. So we can help, again, accelerate that time to ROI. That's a hard capability for institutions to really replicate in-house.

Mark Leher:
And then the second I would say is our human touch. So just like I said, so we have human touch on the data and eyes on the data and helping with that validation and governance of that. We have human touch with our clients, our client success team. When we talk to our clients, that is always one of the reasons why people work with Segmint is that team, because they're having conversations with you as the client, but they're also having conversations with hundreds of other institutions that we work with on a day to day basis to understand that the challenges, and Jim, you put it best, to help people avoid some of the pitfalls.

Mark Leher:
I think every institution that we are working with is facing some of the same challenges of there's pressures from fintechs, there's pressures from Google or Amazon starting to get their hands into the financial services space. But the advantage that the institutions have is they've got all that data. The fintechs want the data, you already have it. And so we can help make that data actionable and kind of ward off some of those threats. And Jason, maybe it's a good question for you where we've helped you guys.

Jason T. White:
Yeah, I'm nodding my head and I'm giving a smile because I do feel Segmint is an extension of our staff, right? I don't have to have that staff on-site. We have a very low dev shop, very low analytics right now due to the partnership that we've created. So, kudos.

Jim Marous:
That's a key element is that as I talk to financial institutions, if they have to put two people on staff to manage a vendor that's going to be helping them in any solution, that takes away from other things those people can do. And to have a partner that can run down the field on their own without you also holding on the ball the whole way makes it so you're freed up to do more the strategic thinking, more the business planning, more the tactical planning that's needed to make this all succeed.

Jim Marous:
Jason, Mark, I want to thank you so much for being on the show today. I appreciate your time and certainly your insights. It's always great to hear success stories and even one that's in process. And just for anybody who questions it, the digital transformation journey is not a destination. It's a journey and it never stops. And as Jason said earlier, I think it's a long term marathon, not a sprint. And oh, by the way, there's no finish line. So you're never done. You just keep on enhancing it. So again, gentlemen, thank you very much for being on the show.

Jason T. White:
Thank you.

Mark Leher:
Thank you, Jim.

Jim Marous:
Thanks for listening to the Banking Transformed Solutions podcast, a new banking podcast that focuses on innovative solutions for financial institutions. We would like to thank Segmint for being the sponsor of today's show. If you're a solution provider, why don't you discuss how you can help bankers and credit unions executives solve a major marketplace challenge. Drop me an email. We're keen to help.

Jim Marous:
This has been a production of Evergreen Podcasts. A special thank you to our producer, Leah Longbrake, audio engineer, Sean Rule-Hoffman, and video producer, Will Pritts. I'm your host, Jim Marous. Until next time, remember data analytics are the foundation of a strong digital banking transformation strategy.