In this episode of Lykken on Lending, David Lykken sits down with Steve Butler, President and Chief Revenue Officer of True, to explore how AI is rapidly reshaping the mortgage industry. From eliminating tedious manual tasks to delivering real-time, trusted data, True is on a mission to empower lenders with fully automated, background AI agents that work invisibly—but powerfully—behind the scenes. Steve shares his journey from engineering to mortgage tech, digs into why past technology efforts often failed, and explains why now is a critical moment for lenders to embrace AI that truly works. If you’re looking to cut costs, boost productivity, and refocus your team on what they do best—this is the conversation you need to hear.
[David] Folks excited to have Steve Butler of TRUE, He is President and Chief Revenue Officer for TRUE. He works directly with the executive management, the team and business strategies, a number thing. And we’re gonna be talking with Steve about this exciting company and our new sponsor and Steve, welcome to the podcast. Good to have you here, Friend.
[Steve] Yeah. Hey David. Thank you very much for having me. I’m excited to be on your show. Really am.
[David] Yeah, I’m excited to have you here because one of the things that we do as a consulting firm helping companies is reduce costs, increase efficiencies, and increase productivity. And that is really at the core of your mission. And so I can’t wait to get into that about the company. But before we do, I want our audience to get to know Steve Butler. Tell us a little bit about yourself, Steve, and your background.
[Steve] Yeah, no, happy to do that. I’m actually a computer engineer by education and I did it.
[David] Forget it, you got too good personality for me. I tease all my computer engineers. There’s a lot of good computer engineers with great personalities.
[Steve] But after doing that for several years I moved into sales and marketing and eventually leadership and really for the last 20 years, I’ve been building and running companies in the last 10 in Mortgage Tech. And the thing that’s interesting, and I look at my career and I know we all look at it at times and I’ve always taken this difficult path, and what I mean by that is the companies I kinda lean towards have this really disruptive technology. They’re only successful if they bring that to market. So they have to innovate on the go to market side as well. They gotta figure out how to get the consumers to use it. I’ll give you a story you may find interesting and years ago, we all have these kind of companies where we start off, we learn everything we learned back then, and we use it today. I worked for a company, it was a startup. The system cost a million dollars and it was a third of the time, it didn’t work. It was the quality was so poor. Wow. And, and but the problem was this, when it was running, it was 10 times more productive than the legacy solutions it was replacing. So if we could get a company to embrace it. They would get a tremendous lift. So much of my career and back then was trying to figure out how do I overcome these quality, ease of use, cost issues to get adoption and so I built a lot of tools back then and so that’s the background I bring into this AI world is how do I get, how do I get this stuff embraced, into a community that’s had a little bit of history with technology that hasn’t been totally positive. Yeah. So anyway.
[David] That’s so true. That’s a great story. A million dollars and it worked, and it didn’t work one third of the time, but the third, the two thirds that it did work made well worth the investment. Fortunately we’ve come a long ways since those days. We have most of our technology working, but it’s too expensive, Steven. So we’re looking for solutions to do this and AI has got some wonderful promises. Tell me a little bit about what you understand to be TRUE’s principle that upon which they’re founded, the purpose upon which they’re founded and their goals, objectives,
[Steve] This company set off and said, most of the time today, when you’re trying to get data and document, getting data off of documents, you’ve gotta send it somewhere, get a human to review it and approve it, right? and fix the problems. This company said, why don’t we solve the problem where there’s no humans required? Can we do it as a purely technology solution that makes it scalable, It makes it real time. There’s tremendous benefits if you can do it that way, very difficult problem to solve, but that’s been the mission and over the last 10 years, they’ve basically got to that result now where you can basically, without any humans. Get the data off of your documents and now you can drive a much faster loan manufacturing process as a result. So that’s been the mission and it’s all about AI to get there.
[David] Alright. More and more AI coming outta the market. Steven that we’re seeing or hearing about that, and there’s others that do the data scraping and the, that what makes you unique? Is it the level of accuracy that you have, the speed in which you do it, the cost in which you do it.
[Steve] I think it, it is the proprietary solution that we, it is, there is many engines here. There’s multiple AI models at play. There’s a lot of things going on to actually get it. But it really is the idea that, I can take data coming in and I don’t have to go send this someplace and have it reviewed. I don’t have to burden the users inside the lender. I can just basically let the technology do it. So it’s purely a technology based machine space solution. And so that’s what makes us special. But of course, on top of that, we’ve built a lot of decisioning solutions as well, because you can collapse the whole thing. Not only do the data, but now I can basically give you an instant income or an instant result. And so now you’ve got an end-to-end solution.
[David] Stephen, many lenders have been disappointed by their technology promises in the past. A lot of promises that just quite honestly failed to deliver real value. Why do you think this is?
[Steve] Yeah, no, it’s a great question. I talk to a lot of C-suite executives and owners of lenders, and they do have a jaded view of technology. The reality is that, for the last 20 years, the cost of manufacturing loan keeps going up, and they tell me, and yet today I have hundreds of dollars per loan in the technology that I’ve licensed to essentially stop that cost from going up. So is AI gonna be just the next shiny jewel? Is it gonna be the same kind of thing? But I will tell you, David, that I dug into this deeper and I found two systemic problems, I think. And the first one is that, lenders today, and I’m thinking mostly the independent mortgage bankers are sales powerhouses with some operations. They’re not loan manufacturing powerhouses with some sales organizations. And by that I mean you. You’ve gotta be careful how you bring technology to the company and so these top down decisions that have been made over the years, the C-suite says, let’s give the manufacturing guys the operation guys some tools guess what? Those tools change workflows and if you don’t have sales and lower, there you go. If they’re not embracing it, then that basically, it’s not gonna be used. And so you cannot top down. You gotta get the user community involved. The second thing that I caught on was that there’s so much of this, boil the ocean. Let’s rip up the old process and bring in a new process. Let me tell you, if you’re a manufacturing outfit, you never do it that way. Manufacturers are looking for gaps in the process to automate, so I, again, I think you have to, a mortgage company has to think like a sales organization and get them involved, but also think like a manufacturer in terms of how they bring it on.
[David] Which really involves process. One of the most important things is if you just throw a solution, a technology solution, into your opts area and you haven’t reinvented your processes. That work in synchronicity with that new technology, you just flushing money down the table and really honestly hurting the efficiency you have as an engineer. I know. Talk to this because I know you see this as happens so often.
[Steve] Absolutely there really is this need to get the users involved to figure out the new workflow. And by the way, the workflow has gotta be something that’s a lift. It can’t be, it can’t be more cumbersome. So much of this is, I think some sins of the past related to trying to do too much and not involving the right level of users in the decision process and in the design process and so we have to learn from that when we go to AI because we’re repeated otherwise.
[David] Yeah, I think you raised a really good point. The motive is good by the executives that are signing these agreements to take on this technology, but it’s the execution. So many decisions that are made are good decisions, but we fail to execute on it. And it really starts, and then, so that’s, I wanna say kudos and grace and mercy of the people have made the decision to have at work. But I also wanna to challenge the operational people that are listening to this podcast in our interview right now, because many of them have been handed a new technology and they have not spoken up, and they have not said this has, we have got to reinvent the processes and your expectations, executives that bought this for us. Thank you. Sometimes they were involved, the operational people were involved, sometimes they weren’t. But a lot of times the opts people just take it and they do the best they can to implement it, but they don’t really realize what has to be done and they don’t speak up adequately for a lot of different reasons and that comes into culture and leadership, and that’s a whole another topic on it but I think it’s something. Any follow on thoughts to that.
[Steve] Yeah, David, one of the things that I discovered, which is hard to find any one person that understands the process you might have to get a half a dozen people in a room to actually understand what their end-to-end process is. So, people own an area, and you’re right, they don’t speak up. They just say, okay, I gotta use this. I’ll figure out how to make it work and sometimes figuring it out actually slows things down. It actually adds more cost, it’s a difficult problem because the mortgage operations, they’ve cookie cutted it up, and no one really understands that whole process end to end.
[David] I’m a process guy. I love analyzing. We do a lot of business process mapping using different tools like that. We use lucid charts and I love that I give a shout out to Keith Polaski over at Radius Financial in Boston. He’s probably one of the most intentional people I’ve had the privilege of working with, and their costs are down because they’ve been intent on this. So, we’re talking more and more about AI these days. Can AI finally change this pattern and really drive measurable impact?
[Steve] I think it can, and I’ll tell you why. Because if you think about the technology of the past, it was like giving an app to a user and the app makes the user more productive. Okay, that sounds good. On the surface, the problem is there’s a training burden. There’s an ongoing refreshing, some of these tools are so complicated, so many features, especially in mortgage, you end up specializing on it. Now you have a new hire that just specializes on the LOS, so the POS or the income calculator or whatever. And so there’s a burden there and that’s one of the things that holds back adoption. AI done right, is a background worker. We have to remember that.
[David] Explain what you mean by a background worker. I agree with you, but I wanna make sure our audience understands what you mean by those words.
[Steve] Yeah. So a background worker is this tedious work that is just being done without any humans having to drive it, teach it, coach it, it just working. So the LO comes in and basically sees all the documents and data in the right place in the LOS and they didn’t do anything about it. The underwriter basically sees all the calculations are done, they just have to go in and look at them and approve them and make some decisions. It’s doing tedious work in the background without any, so now you really have an as a true assistant rather than an app and that’s why I think AI can be very different. Now, of course it can’t do all things, but if you can find those areas where it can be a background worker, that’s where you get your big win.
[David] Yeah. I love how you mixed in your, the name of your company into that explanation. True to true. To get a TRUE AI can make such a difference. And I agree with you that it needs to operate in the background. If you have to hire another assistant or a human to run the AI, something’s not working right. And I think that’s one of the things I’m so excited about our partnership is, I’m excited to help people become more aware of just how you do that. So what is the best strategy, Steven, for implementing AI successfully, and where should lenders start? It’s oftentimes the starting point where we mess up, right?
[Steve] Yeah. So I think the best strategy is to look at your process and find those highly manual gaps and there’s plenty of those where there’s a lot of manual work and then find out if you can find an AI agent that can take that on that intersection of an AI agent, that can be a background worker to tackle that gap. So, the pace to start and this is what TRUE does, so I’m gonna emphasize, but it really is about getting your data right. Data is the lifeblood of the whole thing. You can’t make any decisions about a loan until you know that you’ve got trusted data. So what we do at TRUE is we generate trusted data automatically as a background worker.
[David] And it’s working in the back. You already described the background. You used the word AI agent, the word agent. I’ve heard thrown around a lot and I’m not sure that I totally understand what is meant by an agent, AI agent focusing on the word agent.
[Steve] Yeah. The best way to think about an agent is that background work. You have AI assistance, so they’re basically like an intelligent app that’s helping the thing, but we’re talking about trying to make it totally background so there’s no burden of training and coaching and oversight by the human. So, I lean towards agent because that’s when it’s actually that TRUE background worker, right? So think of it that way and so you, if you can find places where an agent can go in and automate a gap in your process, you’re gonna get an immediate lift, right? And an immediate ROI quick win. And then you start on your journey for doing other things after that.
[David] Is it focusing on the process? is that where you say the place to start?
[Steve] Focus on the process and really go after the data, get the trusted data because everything stops there anyway. That’s almost low hanging fruit today. Get the data right, and then you can get into order, then you can use AI for decisioning.
[David] How long does it take, what’s a reasonable expectation for the time, the duration it takes to really do that and do that effectively?
[Steve] Yeah. We’ve created it. We’ve packaged it up as solutions because otherwise it does become. Okay, I got this great technology, we don’t wanna apply it. So, we have what we call instant indexing, instant extraction, instant income. So you get those solutions and you just take them on. So within 60 to 90 days, you’ve got that function automated with your agents in the background and so this is how I think it really needs to be. Forget about these big projects, where you have to figure out what we’re gonna do. Just take a solution that’s already pre-packaged and ready to go.
[David] Yeah. Why is now today? Such a critical time and moment for lenders to adopt ai?
[Steve] Yeah. This industry is so ripe for disruption. I’m gonna tell you that you know this better than me really. But anyway, it’s a very ripe for disruption because the fact of the matter is it’s unsustainable for cost to keep going up year after year. It’s just not gonna, just not gonna work. So a few big lenders, have talked about spending hundreds of millions of dollars and they’ve actually got themselves well-armed with a different cost basis. A different time basis for their loans and a better borrow experience and so they’re armed to go after market share. So, I think there’s some urgency for lenders to get going to protect their share. But the other thing that I see that’s worrisome and causes urgency in me is that you know that keeping, attracting and retaining your loan officers is critical in this business and so if you’re a loan officer, you go in, you gotta do all this tedious work dealing with documents and data, or if you’re an underwriter and you have to do a lot of manual calculations and all that, you’re gonna think twice about, do I work here or do I work with a company that gets all that for me as AI agents in the background.
[David] Yeah. Now what you’re really getting to is the recruiting top talent and getting AI to do the work that is the tedious stuff. While some humans may be really good at that and find their identity in it, the way the industry is moving, where we’re moving as an industry is more back to the relational side. We, as humans should be involved in the relational side, whether it be an underwriter communicating to an originator, communicating to the consumer. That’s where we should be focusing and letting these engines, these agents, AI agents working in the background, doing that tedious work, but doing it without the human flaws.
[Steve] And you said it perfectly, David. I’m an lo I wanna work with my borrowers. I wanna give them white glove treatment, but I can’t do it if I gotta spend hours doing tedious work. So if I can free that up I’ll book more business and that’s what I enjoy doing. It’s exactly it.
[David] Yeah I, this is something I discovered early in my career is important for us all to focus in on where our, we are best at. For me, I’m a relationship guy. I love doing podcasts. I love talking to guys like you Steven and I got bogged down and it really impacted my productivity. Not that I didn’t do it that well, to be honest with you, and it’s when we have these kind of tools, it really strengthens those with strong relational skills. I would you agree with this statement that the companies with the future that are gonna succeed are those that have found a way to implement AI and getting humans back onto where they should be and working on the relationship component.
[Steve] Put them in their strengths. If you can get back in their strengths, their core strengths, you know that if you’re a customer support person, I’m talking with customers, this kind of a thing. That is where the success is gonna happen. And the great news about AI is it’s really good at doing tedious work. Yeah. It really is if you’ve trained it well and that’s what we’ve done. And I think that’s the future. Really do.
[David] Yeah. I get excited about this new world that we’re in. I’m 74 years old and I’m looking at 20, 51 years in the industry, and I’m more excited about this industry and what we could do because ultimately it’s about creating home ownership, a successful, less burdensome home ownership journey getting into home ownership through real estate finance and I think what you’re doing is really commendable and really exciting for what this could be doing for lenders in the future.
[Steve] Thank you, David. Yeah, we’re really excited about what we’re doing and we’re getting some great success from this.
[David] Yeah. Give me, do you have a couple testimonials real quickly? If some stories of clients, you don’t have to name them if you don’t want to, you’d welcome to if you want, but is there any sort of stories you go oh, Dave, let me tell you a story about this one. We have had. I already talked about my good buddy at Radius Financial up there is Keith. Do you have any stories?
[Steve] Yeah no, certainly. Yeah. I’ve got a customer, I talked about that 10 x in my early opening with you, a customer getting to 12 x, they used to do a loan an hour. Now they’re doing 4 loans in 20 minutes, 12 x we’ve got other customers where the loan officers have freed up so much time because everything’s just happening for them in the background and we’re talking large scale lenders. So, I think the time is now for this to happen and I think this is a great discussion that we’ve been having to get that message out there, I think.
[David] Yeah. I’m excited to be partnered with you now, Steven. I’m really excited to have your message told on my podcast. I want to champion you out there in the marketplace. Listeners, get ahold of Steven, get to understand what this company is about. For those that wanna do and I’m hopefully thousands will, Steven, how can they best reach you?
[Steve] They can reach me through email. sbutler@true.ai is probably the best way. Our website is a great source of information about how to take on these solutions as well. Some testimonials on that website. We’ve got a great podcast and a big podcast, great blog on there as well that you can read a lot about what we’re doing. That’s probably the best ways to learn more about TRUE.
[David] I encourage you all to get over to the website and check out the blogs. I’ve checked through it all. Great information there, and I, it’s a great resource for people exploring how to become more efficient, reduce costs, and get your people back doing what they do best. People. Steve, what a joy to have you on the podcast today. Thank you so much,
[Steve] David. Great questions. Really good discussion. Really enjoyed this.
[David] I did too. I’m looking forward to a lot more.
[Steve] You bet.
About the guest:
As President and CRO at TRUE, Steve works directly with the executive management team on the organizations business strategy and is responsible for all aspects of the firm’s revenue generation team. From sales, to marketing, partnerships, business development, and customer success, Steve’s tech-seller approach and customer centric vision are critical to TRUE’s continued expansion into the lending industry.
A true believer in AI, Steve has decades of experience running revenue organizations and building valuable tech companies. Prior to joining TRUE, Steve was CEO of GoDocs, a leader in commercial lending automation, founder of AI Foundry, and led revenue organizations at a variety of successful technology firms. Steve has a BSEE from the University of Rhode Island.