Tyler Barron
Whenever you take a very large technology, you categorically speaking like machine learning and kind of lump it into just one area like decisioning then it kind of becomes a little dangerous to work if I kind of had to put my finger on it. You know what is kind of the broader fear and concern is just lack of understanding and knowledge.
James Robert Lay:
Greetings, and Hello, I am James Robert Leigh, and welcome to episode 280 of the banking on digital growth podcast. Today's episode is part of the exponential insight series. And I'm excited to welcome Tyler Barron to the show. Tyler is the Chief Revenue Officer at Encapture, the intelligent document automation platform that helps companies financial brands be more efficient, and even more customer centric. Tyler has over 10 years of experience within SAS and enterprise technology. And he has a proven record of success for developing and executing strategy, while also creating repeatable frameworks to accelerate revenue growth. Welcome to the show, Tyler, it is good to share time with you today, buddy. Yeah,
Tyler Barron:
Thanks, James. Glad to be here.
James Robert Lay:
You know, before we get into talking about automation, and this this terminology machine learning that I know has a lot of people probably feeling a little bit confused right now. What's good for you, personally, or professionally, it is always your pick to get started on the show.
Tyler Barron
Yeah, I mean, lots of good stuff going on. Over here. I mean, professionally, you know, going on on three years here in capture. So you know, the like, that's been a really strong journey. And then we were chat that up here earlier, before we got kicked off, you know, personally coming up here on 10 years of marriage and got to healthy boys. And just feel like I'm in a wonderful seasonal life here personally, and I'm still very blessed from that standpoint,
James Robert Lay:
That's fantastic. And you know, when you think about the journey that you've been on, whether that be personally with your marriage, with your family, with your kids, or professionally, it is a journey of growth, and there are different seasons of growth. And if you think about you know, to start off this decade 2020 that accelerated a tremendous amount of quote unquote, digital growth for financial brands. But if I look back, you know, over the previous year 2022 Going into 2023, I think the big theme coming out of that is what I'm framing around adda AI, data, and automation. And I like to use the word adda and give this name because I think it's a little less scary for people, particularly financial brand leaders to, to think about to gain clarity around because the antithesis to clarity, it is confusion. And, you know, there's this idea that I was mentioned before machine learning, I want to start here to provide some perspective for the dear listener to demystify these two words machine learning because right now, from all the research that we've been doing both primary and secondary, they mean different things to different people. So can we start hearing de-mystify quote unquote, machine learning,
Tyler Barron:
Categorically, it's a very broad term, whenever you think about that, it does kind of create a little bit of fear and risk and uncertainty as it relates to that, especially in the banking space. You know, for Ross, just broadly speaking, you know, really what machines learning is doing is it's it's automating the task of what what humans could be doing, which are some of these lower value operational type tasks. Ultimately, these systems can be trained to get smarter over time, and continue to mimic those tasks. But, you know, I do think it kind of gets, you know, brought into some negative assumptions really quickly around, you know, is this going to replace people's jobs? Is this going to create inherent credit risk, regulatory risk, or all these different elements but, you know, in its most simple terms, it's really just a, you know, operation, you know, time and task saving piece of technology.
James Robert Lay:
Why why is that? Do you think that people might have these misunderstandings, these, these misconceptions what, what is that rooted in?
Tyler Barron:
Yeah, I mean, I do think that there is some some valid concerns to where there have been some cases in the past where, especially on the lending side of things as it relates to decisioning, to where these models have started to do some have some negative social impacts to a certain degree automatically, or creating some bias or things like that, you know, then these banks get dis regulatory issues, or they're not compliant with with their fair lending policies or guidelines. So there's some things that have come up, that do create genuine concern. So I don't want to like be dismissive of a of a valid concern. But also, whenever you take a very large technology, you categorically speaking, like machine learning, and kind of lump it into just one area like decisioning, then it kind of becomes a little dangerous to work, you know, we're in, we're gonna hold you holistically different category, which is intelligent document automation, there's probably 30 different pockets of these things that roll up to that broader term. I mean, I will say, if I kind of had to put my finger on it, you know, what is kind of the broader fear and concern is just lack of understanding and knowledge. And look, I'm a guilty party as well, that throws these buzzwords around and, you know, really try to push innovation, you know, into the industry and talk about these things. And without really slowing down and breaking it into very simple terms, in terms of what the solutions actually doing, what it's doing with the data, what you could what you could control what it can't control, what are the real limitations. So what a lot of pie in the sky, buzzword type stuff without really pragmatic, excellent explanation, and application of what that's actually doing? Well, let's,
James Robert Lay:
Let's do this right now. I want to slow things down, back to your point. And let's talk practical application. Let's go beyond buzzword bingo. And for the lenders, for the leaders who are listening right now at a financial brand at a bank at a credit union at a FinTech, what are some of the biggest opportunities around intelligent document automation, that are available for them to either A, create something new capture may be something that they already have, but they're missing out on or be capitalize on a strength that they already have to do it even that much better going forward. So let's use those as our three frames and break each one of these down. So what's something new that that you see that they could create? Through this idea of not not machine learning? Let's throw the buzzwords out but Intelligent Automation here from an operational perspective?
Tyler Barron:
Yeah, that's a great question. And I think if you kind of zoom out a little bit more and talk about what's relevant from a macroeconomic standpoint, and really kind of put the technology in the lens of what's happening in the world of banking today, as it relates to the financial markets, the regulatory climate, just the general business climate. And you kind of think about that Well, coming out of coming out of COVID. James, to your point, you had a lot of acceleration of digital transformation, banks and talked about it for 10 years. And as like, all of a sudden, everybody got hit in the face. And it's like, we need these things to reach customers where they are today. We can't wait three, four years anymore. It it moved all that stuff forward. And then kind of coming out of that you kind of had this market correction to where, you know, banks need to cut down on cost margin compression is happening with lending. It's like how do you improve operational efficiency around this? And then the third element around the mica macroeconomic climate is you're seeing a lot of regulatory scrutiny updates of older rulings, new rulings, for a lot more enforcement around those things due to the lending boom, that happened. It's like, Okay, now we're starting to see some more delinquencies. How do we ensure that that these people should have got these loans in the first place? So get back to your original question? I think probably one of the lowest hanging fruit areas is a augmentation of existing processes around fair lending and compliance. So not to get too far down in the weeds, but, you know, common practices around collecting demographic data for mortgage to make sure that there's no lending bias there with like the home mortgage disclosure act Comdata. You or with small business lending with the Community Reinvestment Act, or the future Dodd Frank 1071 ruling all these all these rulings are based on collecting demographic data from borrowers. And ultimately what's happening behind the scenes is that's a lot of data. You know, you're you're lending 10s and 1000s of loans, you're collecting hundreds of data points. And ultimately, there is a lot of discrepancy between what's in these these sources of truths. The actual lending documents, the business systems, the reporting systems, whenever the government regulators look at this stuff, and what we've heard over and over again, is that there's teams that come in at banks that do nothing but spend time scrubbing this data, right. So, you know, this compliance data scrub for things like hummed and CRA, is such low hanging fruit. It's, it's a task that, you know, compliance, people are one they're hard to find. They're relative, they're not cheap, either. And just just speak candidly, nobody out there is you preaching to the next generation, how awesome it is to go into baking compliance. And so there's there is a shortage there as well. And it's like, you're you're spending time doing things like scrubbing data, whenever you need these folks partnering with the business on how do you you operationalize and mitigate these risks from the regulatory pressure. So that's, that's the simple augmentation of an existing process, like a good use case of like, hey, this 100% could be almost fully automated.
James Robert Lay:
I like the way that you frame this around an augmentation of an existing process. I would, I think about things as optimization, augmentation optimization, because we're taking something that is good. And we're making it even better going forward. And we're creating value, we're freeing up people's time from the rote from the repeatable, I think more value can be created from their expertise, let the machine let the automation do all of the quote unquote, the hard work. And then we can get back to more of the critical thinking to do even better as an organization around these points of compliance. What's your take on that perspective there?
Tyler Barron:
Yeah, 100%. I mean, I think that, that then this kind of goes back to the original question around fear around machine learning and automation, it's not going to replace people job, it's going to empower knowledge workers, it's going to it's going to take all these lower value tasks that you're hiring expensive people to do, and and allow them to focus on actually thinking and optimizing the business. And, and so I think that, that whenever we reframe that, people are going to become more accepting of these as tools as, Hey, these are things that are here to make my job easier, you know, so I'm not having to work 60 hours a week.
Tyler Barron:
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James Robert Lay:
Let me take this a little bit further here. Because this is something that I've been thinking a lot about, as I've been writing my second book banking on change that I have framed around the four exponential growth environments, there's a there's an environment, bacteria to the point of seasons, seasons of growth, there's there's seasons or environments that we can be learning, we can be thinking we can be doing, and we can be reviewing. And if I think back over the last maybe 20 or 30 years of business, it's very easy to fall in love with what we do, and even maybe at a deeper level, attach our identity to the work that we do. Where I see probably one of the greatest challenges for transformation when it comes to people in the age of AI and automation is to detach from the doing so that our self worth goes beyond Hey, this is what I do. Now, if you love to do all of this deep level compliance work and scrub this data. Well, that's fantastic. But hey, did you know that you could do even better if we enter in automation to free you up to create space and time for you to pause, to review to reflect what you've done, to learn through those experiences to think about how you could do even better and as a result, you're going to grow personally Actually, the organization's going to grow, your team is going to grow. What? What do you think it is that then just think about yourself too. And I think that's the best the best perspective to think from. How do you because you are Chief Revenue Officer growth is part of your DNA? How do you continuously let go of things from the past to create space to grow going forward into the future?
Tyler Barron:
And James, that's a great question. And honestly, quite quite relevant. For some recent self reflection I've had, you know, all of us kind of do that, at the beginning of the year, I haven't been here at any capture for three years, and we we've three extra revenue since since you know, we had a growth equity investment brought in a new CEO, I joined shortly after him, it's been a great journey. But you know, we're private equity backed business, very metrics and data driven, we process engineer a lot of things we, we measure where high performance, high accountability. And, you know, the thing that that is easy to get caught up in is tying yourself wore to do to that all the time of the ebbs and flows of just your work, right. And it just the nature of, of running a business and all those things. And the thing that I've really challenged myself here lately, to kind of take a step back on is to really kind of think about the things that have an impact that ultimately result in those things. Yeah, and those things are the relationships I have with people here to capture, you know, my, my executive peers, folks on my team, and my really spending enough time with them mentoring and coaching them. And in really, really making sure this is an impactful experience for them. And in helping them be successful, because ultimately, all those metrics and data, it's just a byproduct of that. And then the other thing, too, is slowing down and really listening to to our Bakey customers more. So we've really slowed down and are doing standing monthly. In fact, we just started doing this six months ago. And that's what kind of allowed us to make this, this pretty good pivot to focusing on compliance was, we said, hey, every single month, all of our key caps, we're going to have standing meetings with our executive sponsors at the banks, it's gonna come in agenda free outside of, we want to know what's important to you right now, not as it relates to machine learning, not as it relates to in capture, but just help us understand how, how the bank is thinking about their business right now how they're approaching this. And, and then from there, you know, we can we can figure out how to help them achieve their goals. And so, you know, it's, it's challenging, whenever, you know, I'm wired to, to measure everything, data metrics, you know, everything's a big math problem to me in a way, and it to take a step back and say, hey, look, these are just a result of, of listening, caring, good relationships, and doing the right thing. And, you know, I don't know why that's, that is such a common sense thing. And, but yet, bringing that to the forefront and kind of taking a step back, I felt like he's really had a big impact just on me personally, like here lately, just, I kind of just feel like a lot more stress free to where it's like, hey, you know, I'm doing the right thing. We're doing the right things. And then also just seeing the positive impact with, with folks here and in capture, and with our customers to where, you know, at the end of the day, we all want to be appreciated. And, you know, you have to earn that right, and slowing down and spending time and just talking about how can I help you? Yeah, is a it's, I don't know, I don't know why it's, you know, him can slip away or you can lose sight of that. But
James Robert Lay:
Because I honestly I think it's we get so busy doing and before you know it, that doing that, that that sense of quote unquote busyness that becomes the standard operating norm. And if we step outside of that, it feels different. And because it feels different, it feels uncomfortable. So what do we do we want to go and do more work back to your point of the compliance officer working 50 6070 hours a week. Is that sustainable for the long term, you can sprint and really work and grind for a period of time. But I think one of the big lessons that has come out of the whole COVID experience around atah around automation around data around AI is that you know what? If we learn Learn, and we must create the space to just pause. So that we can review and reflect and learn through either those experiences or learned through other sources. It's the learning that helps us to begin to see things differently than how we saw things before. And when you start to see things differently, you're going to naturally as a byproduct, begin to think differently. And that thought that thinking is then going to influence you to do differently than how you did before. And to me, I look at the idea of Intelligent Automation, as a teammate to create that space and time for us to be for lack of a better word, even better people, because we have that ability to do things we weren't able to do before, you know? Yeah,
Tyler Barron:
I mean, it removes friction and drag, right to where the where you it's challenging to come up and, and have, you know, more self reflection, learning strategy coaching all these elements? How do you provide a better customer experience all these things? If you're just drugged down by these by these manuals? And the thing about like, the compliance examples, you have to do it? Yes. I mean, if there's anything that can potentially in the bank, it's that it's table some. Yeah. And so you, it is kind of a catch 22 To where, you know, ultimately removes friction. And there's a lot of things in the automation space as well, on the other end of the spectrum around your customer experience and digital journey around, you know, lending or account openings to where those things can, you can remove friction from the customer there as well. And it gets them through a process more pleasurable and faster. And, and ultimately, there's a better business outcome to wear, higher conversion, less cost all those things, too. So it is this element to where we're seeing machine learning removed, remove just a lot of friction and clutter, like clutter drags probably the best. Yeah, that's word for it.
James Robert Lay:
You know, what you're talking two sides of the coin, here, you're talking first and foremost, optimizing the internal employee experience through augmentation around automation. And then second, now we're about to go down a path to the other side of the coin, which is the external CX, the customer experience, or the MX if your credit union, the member experience. And experiences as we define them here at the Digital Growth Institute are nothing more than well defined systems and processes that have been a strategically thought and mapped out, be applied. And then the, the opportunity is the See, it's the optimization of those experiences, hopefully resulting in a positive emotion or, or potentially negative emotion. But if it's a negative emotion, well, let's learn from that, to then do even better going forward into the future. So thinking about this external customer or member experience around Intelligent Automation. Where's an opportunity here that you see from your perspective of the world?
Tyler Barron:
Yeah, I mean, James, all the best ideas come from come from the banks and credit unions that are they're not in captures ideas, they're their ideas that they brought to us. And this was actually a FinTech lender, that came to us doing a lot like very large volume, personal loans had just IPO. And, and was literally doing hundreds of 1000s of these personal loans every single month. And their whole business model was, hey, somebody applies online, we ask them for information around, you know, proof of identification, proof of income, proof of residency. And, you know, if we can't get that information in like, less than five minutes, they'll go get it, they'll go get it somewhere else, they'll go get a loan somewhere else, they'll go do business with someone else. And so they came to this idea, they said, Okay, your your technology has the ability to take the supporting documents, you know, IDs, driver's license, passports, your bank statements, things like that,
James Robert Lay:
All of the oiling, frustrating stuff that people this stuff, you got to dig
Tyler Barron:
Through and has the ability to basically extract data out tell it hey, is this what what the customer saying it is it does the information match the application? They said, y'all are telling us that can do this? They're like, Can we can we augment that into our existing digital application for meaning that instead of saying, hey, you've been pre approved, we're gonna send you a message. You know, I think they were used to text messages to where it's like, you know, somebody's gonna reach out asking you to upload these documents via your cell phone. Pretty slick still, right? Yeah. But but their whole deal was there. Like if we can keep somebody in that flow? Yep. And immediately get them to upload those docs. If they submitted something out of date, we can ask them to resubmit it. They put their thumb over it, you know, all these things like, we've all been through this with, you know, opening an opening or a mortgage or to open an account, whatever it might be. I think one thing is was really relevant to these folks is just the nature of their business was so had to be so sharp, to where it's like, they're like, look, we've got to have somebody in this flow, because abandonment rates are everything to us. Yes, like, anyway, anyway, we can reduce that is material. And then there's operational cost reduction to it's, you know, hey, you've got folks on the other side, manually looking at those documents being like, does the income in the application match the W two or the bank statement? Yep. And all of that can be done through machine learning. And that the coolest thing is, you could just keep somebody all the way through that digital flow all the way till that money sit in their bank account, you got happy customers. I personally think that that's a very impactful experience. And then to bring this all full circle, if you're collecting good data up front, this compliance issues on the back end, usually aren't going to exist, because you've kind of done this, this QA QC upfront by validating the data that's been put into the system against the source document, as opposed to human error being introduced early. So it's, it is this big lifecycle of data.
James Robert Lay:
This is the I would say the number one problem that we see. And then we provide guidance and recommendations and coaching around because what good is filling the top of the funnel with more traffic, who doesn't matter, the sources of the traffic? If we're losing all of that, at the bottom of the funnel? There's so much I think, you know, back to your point, low hanging fruit to capture there. I want to get your take on this as we start to wrap up roadblocks. What are the things? What are the roadblocks? What are the challenges that hold financial brands back their leaders back their lenders back from really optimizing, whether that be internal systems and processes to make the employee experience that much better, or external experience and processes to make the customer the member experience that much better? What is it that holds them back from from taking the steps around Intelligent Automation?
Tyler Barron:
That's a great question. I mean, everybody gets it at the business level, I mean, for a solution like ours, ultimately, we'll go in and have a calm conversation around the ROI with with the with an executive leadership team. And they look at this stuff and kind of to bring it back to like a traditional example. You know, if somebody's working in the branches, a personal banker, and they're having to, every time they open account, do five steps to break up a document, send it to five different departments, you know, we'll present that and it'll be a million dollar savings, no real example from a bank, you know, 30 billion asset banks in Texas, but the CFO told us, he said, Hey, look, these people, like, you know, the ROI makes sense. But like these people, we're not gonna get rid of them. He's like, but this is time that they need to be spending with the customers in the members. Yeah, they don't need to be jacking around doing this. So you know, there's that element that that makes sense. I will say, whenever you really kind of get this into the hopper, a bank says, yes, we want to do this, they want to move forward, the biggest bottleneck that we see is resources. So there is a massive backlog it just about every bank and credit union that we've talked to in terms of projects, and resources, and all of these things. And so one thing that we found is that not many have the appetite for these big two year digital transformation projects anymore. They just simply don't have the resources, it needed to be done yesterday. And so we've had to really adapt our business model to say, okay, yes, there's six or seven things that we could potentially automate here at this bank or credit union. But how do we prioritize break that into low hanging fruit, a kind of deliver that 90 Day chunks, yes. And then also the, you know, not to get too technical, but the world of SAS has has opened up just an amazing toolkit to be able to deliver these these tools faster, quicker, more repeatable, less resource intensive, less expensive, on the bank and credit union side of things, that has had a material impact as it relates to, you know, previous on prem type stuff as well. But I would still say that that's probably the biggest challenge is, even whenever everybody wants to do it, it has funding it's like, and we don't even have folks to support this and do this. And so, you know, kind of looking at this from a more pragmatic standpoint and saying, okay, yeah, we want to do all this. But But how do we how do we break this into smaller chunks? It James, you know, hopefully this is your kind of speaks to something you're passionate about from from a change management standpoint, we found that to be way more effective, because everybody wants to be part of a win. Yeah. And so if we, if we can break this into 90 day, White wins of delivering ROI and success, and value, as opposed to everybody waiting a year, two years until this big bang of value, it's so much easier from an adoption and just just the social aspect of of folks getting behind it and want to embrace it, you know, you usually find one group in there that's like, hey, look, we're willing to be first Yes. And you get those folks successful, and then you earn the right to do more. But, you know, I do think that there is this expectation needs to change from from vendors like ourselves to where it's like, hey, look, it's, it might sound counterintuitive, to not go chase million dollar software deals, but ultimately, you need to focus on how do you carve this up in a way, which sets the customer up for more long term success, quicker value, faster change management, and we've made some really smart adjustments around that. I feel but I just kind of think it's a nature of, of, you know, just something that kind of just slows things down a little bit right now.
James Robert Lay:
So let me let me just share this back out to the dear listener here. Because back to your point, you did pick up on this, I'm very passionate about change management, because as a digital anthropologist, I've studied the intersection of marketing and sells and technology, and then human behavior over the last 20 plus years. And I would say, at this point, in my own personal journey of growth, I am most interested and I'm most intrigued at the most complex technology, even in this age of AI on planet Earth, which I say is the human mind. Because this is going to determine whether or not any type of future growth initiative, you know, gets that buy in gets that acceptance gets that adaption, that commitment. And really, I think even more deeply than that, the courage to commit to move forward with confidence. And, and I liked how you broke this up into small chunks. And the idea of the 90 day when in fact, you know, you're you're, you're leaping ahead into the banking on change methodology, which which I'm, I'm writing around the 90 day growth method. Because if we can get that early, when we get some momentum, we get some wind in the cells, well, that's going to continue to propel us forward going into the next 90 day period of growth. And it's just a different way, I think of looking at the world back to the point I was making before you see things differently. When you see things differently, you're going to think differently. And I've asked this question 1000s of times now to financial brand leaders, I said okay, well, when you think differently, what's gonna happen next 99.99% Say I'm going to do different, I'm going to act different, I'm going to be different. And I say, I understand where you're coming from. But do you mind if I give you a different perspective? And they say, Yeah, sure. I said, to bridge the gap between the thought and then the action, the thought and the commitment, it comes down to feeling an emotion. So you see different, you're going to think different, you think different? Well, then whether or not you act is based upon Do you feel any different because of the desire, the feeling the emotion to then go and commit to do something different, has to be greater than the desire to remain the same stuck in the status quo. And I think back to your point, you're helping people feel the winds. And like you said, everyone wants to be part of something where they're winning. Together. Let's get real practical here. At the very end, as we wrap up, Tyler, always like to send the dear listener off with something that they can do that they can get a quick win around something small because all future growth begins with a small, simple commitment that they can take today. What is the one small thing that you would recommend for them to do next on their own journey of growth? Around what we've discussed with Intelligent Automation?
Tyler Barron:
Yeah, I mean, we talked a lot about this, this compliance component, just the macroeconomic circumstances that banks and credit unions are under. So I would encourage, you know, digital banking leaders to go talk to these compliance teams, to talk to them about these processes. And it doesn't just have to be the compliance team, or any of these folks that are doing any of this work and say, what are the things that are giving you drag? What what are the things that ultimately are preventing you from from doing what you really need to do to move the business forward and create a list of those things? And, you know, from there, you can kind of figure out okay, well, one, do we even need to be doing this anymore? It may have to if we have to, can we automate it? Yeah. And then three, if you can't automate, it's like, okay, well, how do you optimize that beyond automation? But it's kind of funny. We, we list out here, you're here to capture, we get together, we're like, what do we need to start doing? Stop doing? We do these meetings a bunch internally. And it's like, half the stuff is like usually like, Yeah, let's just stop doing that. Yes, you know, and so I would encourage everybody gets to go talk to their teams and just figure out what the things are that are that are creating, creating drag.
James Robert Lay:
Yeah. And I like that idea of having the difficult conversation of what do we need to let go of to continue to grow and if we don't want to or don't have to or don't need to let go of it? How can we look to automate the predictable so that we can humanize the exceptional I'm pulling from the founder of four seasons there. It was a big big part of the Four Seasons experience automate the predictable to humanize the exceptional Tyler this has been a fantastic conversation today. Thank you for joining me if someone wants to continue the conversation, what is the best way for them to reach out say hello to you?
Tyler Barron:
Yet, the best way to reach out to me is probably on LinkedIn. So feel free to phobia connection requests also got a pretty heavy travel schedule coming up with your show season coming up this spring right let me know where y'all are gonna be would be glad to connect in person as well. And James, thank you for today. This has been a pleasure.
James Robert Lay:
Absolutely. Thank you Tyler for joining me for another episode of banking on digital growth. Connect with Tyler learn with Tyler. Grow with Tyler Tyler. Thanks again, buddy. Thanks, James. As always, and until next time be well do good. Make your bed
