Where Construction Loan Risk Hides | ABA Podcast

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Tim Pannell: Hello, and welcome to the American Bankers Association podcast. I’m Tim Pannell, vice president of the Partner Network and Member Engagement. This afternoon, it’s my pleasure to welcome Sean Faries, CEO with Land Gorilla. Land Gorilla is a premier partner of the ABA, and they are a leading technology provider of construction loan management software, giving financial institutions confidence to make safe, fast, and profitable construction loans. Land Gorilla technology reduces the frustrating back-and-forth between loan stakeholders while giving lenders complete control over draw management and reporting tasks. Their proven platform enables faster disbursements and seamless exchange of information between stakeholders all in one place.

Sean is with us today to discuss “Risk Lives in the Gaps.” Good afternoon, Sean, and welcome to the ABA podcast. We’re looking forward to talking with you today and learning more about how risk lives in the gaps and how Land Gorilla can help banks.

Sean Faries: Tim, thanks for having me on the podcast. This is great. I really appreciate it.

Tim Pannell: We are glad to have you here, and a few questions for you, Sean. First question is this: Banks spend significant time and money on construction due diligence. Most feel their process is thorough. Where specifically does that process break down, and why is it so hard to see from inside the organization?

Sean Faries: That is a good question. And I think banks come in different shapes and sizes, and they have different processes, and with construction lending, a lot of the information is really tribal. You learn it from growing up. It’s not like there’s a college or a school that you get to go to, and they teach you all the best practices. But there definitely are best practices that live out there, and I think every institution does it a little bit differently, and I think some do it better than most. And I wouldn’t say that anybody necessarily does a bad job out there when it comes to due diligence. I think the big concept that everybody really understands is that a phone call early on in the process to resolve something is so much easier than dealing with a lawsuit at the end.

So, when we think about construction due diligence, there’s a couple sides to it, and there’s one understanding the the borrower or developer or the the party that’s going to be doing the work—let’s just say it’s the general contractor. And I’d say the other side of that is the project analysis. So, two sides to that coin, and the bank is really trying to understand: Do we accept this risk? Is Bob the Builder over here going to get the home built? Is Bob going to be able to get it built for what he says he’s going to get it built for? And trying to understand that risk. And some places do it, do it great and have a long-established process. Some, I think there’s some out there that really have opportunities to improve that.

But now with AI, there’s a lot of opportunity, and Land Gorilla has been doing this for almost 17 years, and we’re sitting on massive, massive amounts of construction data. And we’ve been doing project reviews and builder reviews for a very, very long time, and with AI, we’re able to leverage a lot of that institutional information. And I think for the first time, it’s kind of an exciting time where you can actually have it all three ways: faster, safer, more efficient, or cheaper, faster, and better, which is really exciting to do. So if banks aren’t already utilizing AI for this, the typical project review—let’s just say project review for for due diligence—depending on the size of a project, if it’s a single-family residence, it’s a little bit easier than a large-scale commercial buildings or multi-family, and those, the bank may go out and contract with a local engineer to do some due diligence. Is this feasible to get built, or is there some risk in it? Now with leveraging our regional data and cost analysis data and AI, we can get a lot of that information in hours, not weeks. And it’s just kind of a pretty fun and exciting time to live with all this information being available.

Tim Pannell: Sean, that does sound very exciting. Could you possibly walk us through a real finding, a case where something passed standard screening, made it into the file, and then X-Ray flagged it? What did the documents say? What did the analysis find, and what would have happened at draw if it had not been caught?

Sean Faries: Yeah, I think the kind of the biggest things that, to take a little bit of a step back, the biggest things that we see with these these new X-Ray products is that it’s able to do something that humans technically can do it, but it it does it a lot better. And that’s the contextual part of what’s happening. Traditionally, you may be looking at the budget, the plans, the specifications, the construction contract, the appraisal. But sometimes you miss the contextual components of it. What does the construction contract say in relationship to the budget? Was there something in there that was an owner’s responsibility that may conflict with what the plans are saying, or the contract says, or the appraisal says? So understanding the interrelationship between all the documents all at once in real time is something that that AI definitely has helped out with, and understanding where those gaps may be in the contract as well.

And then I’d say the other area where it really does a good job is on adaptiveness. And what I mean by adaptiveness is there’s a big difference between a regional homebuilder, right, or somebody that builds one or two custom homes a year. And the way their finances work, the way the risk works, for for example, if the large regional homebuilder has a couple liens or a couple blemishes on their background check or or credit, it’s probably not a big deal if you’re looking at $50,000 worth of worth of issues, right, for for a regional builder. But for a smaller homebuilder, that could be significant, right? So that review needs to adapt to what the situation is, whether the situation is focused on a particular builder or company, or the situation is focused on the adaptiveness of the project. Hey, is this a single-family residence, or is this a 50-unit apartment building that’s being built? So I think there it’s able to do the justification and the math in a way that we really haven’t seen.

When you start thinking about what those examples look like, there’s one that we’ve been using as an example where they had claimed that the homebuilder had claimed, “Hey, we’ve got no employees. Therefore, we’re exempt from workers’ workers’ compensation insurance.” And I think it probably pass the smell test in a lot of situations. But with our new X-Ray reports, it did a digital reputation search, it went on and looked at all the review sites, and it noticed that people were complaining about a particular job foreman. Let’s just call the job foreman Freddy. And there were a couple complaints against Freddy, but Freddy was not listed as a principal in the background check. And then it further did that and went and looked at the state laws on workers’ compensation insurance requirements and the Secretary of State registration, and it concluded that, “Hey, this is a If you’ve got employees, you’re required to have workers’ compensation,” right? And they noticed that, “Hey, you’ve got an employee that’s being mentioned in all these reviews.” So it did something that, unless you’re really good at stalking companies on Facebook and social media, that’s not something that normally would come out, but it really got into the details and validated it, too.

I think another kind of good example that we see is on the statutory requirements. And what I mean by statutory requirements, if you don’t know this, Land Gorilla has a huge statutory library. Kind of our gift to the world, what to do in each state and what those requirements look like, and we’ve spent an absolute fortune, a small fortune, in compiling that information on a state level, right? Here’s what you do in this state. Here’s what you do in that state. Here’s how the lien law works, and it’s just an amazing library. But in Illinois, you can’t sign the construction contract before the mortgage closes. And if you do, the lender can lose first priority. So kind of low-hanging fruit in this review was, “Hey, let me check that out,” and I can tell you, most I don’t think I’ve ever seen a project review that looks at the statutory requirements, right, as part of the due diligence. And we reported back, “Hey, your construction contract’s executed. Um, the bank’s going to be in second position on any improvements that get made. This is something you need to come to a hard stop on and work with the title company on how to resolve the situation.”

So those are two things where you just pick up the phone and probably resolve the issue right now, then cross your fingers and hope you don’t have a lawsuit down the road. And I think another kind of big part of this is the cost, right? If you go engage a local engineering firm, and you’re on the bottom end a couple thousand dollars, on the high end $20,000, $30,000, $40,000 for some of this work to get done. And we’re depending on the product and the customer subscription, it’s we just roll it in. And we make it really easy for you to save a whole lot of money in getting these reviews done. There, I mean, they’re not free, but they’re pretty close to it.

Tim Pannell: Sean, those were some great examples that are very helpful. You had mentioned earlier AI, and of course, AI in banking is a topic most bankers approach cautiously, and reasonably so. What’s the right model for applying AI to a high-stakes underwriting decision? And where does human judgment fit in the process?

Sean Faries: Yeah, I God, this question really has evolved over time. And I think if you would ask me six months ago how banks would be easing into AI, I thought it would be a lot slower than what it is now, and it seems like it’s just such a profound tool and movement that it’s really undeniable. And you see a lot of financial institutions just going headfirst. And what I mean by headfirst is not recklessly headfirst, but they’re pushing policies out quickly, trying to to help get this in the hands of everybody. And I think that’s the right way to go.

In answer to your question about this being a high-stakes high-stakes underwriting decision, the the two ways to to think about this this product is it’s not a typical underwriting decision as it comes to to a borrower, and I think there’s a clear distinction in your regulatory guidance of the use of AI, especially with consumers. This is simply a look at a business’s construction-related components, right? And which is still significant in its own right, and I think every bank needs to look internally and see how this fits with their own internal policies and procedures when it comes to that.

Our X-Ray reports, which is what we’re calling them, all have a human review to it. So AI does a lot of the heavy lifting, but there is a human professional that comes and sits right behind it and checks all the work and makes sure that the square footage and contract amounts and the things that it’s calling out or not calling out are actually true. And I think that’s, at least in the time that we live in right now, really, really important, because AI is not perfect. It’s getting a lot better every day, but we will see a time where it’s riskier to have a human involved in that decision. Right now, it is riskier to have AI involved in the decision. But I think we’re on a clear trajectory where we see those percentages just change over time.

So I think banks have been really well—I don’t want to say ready, but their readiness is the fastest I’ve ever seen in adopting a technology. Usually, we all face a lot of criticism for this space not moving quick enough, but I think AI really has opened that door to a lot of possibilities and just good policy and good change management and being responsible stewards of the information is the name of the game there.

Tim Pannell: Sean, this has been great information, and I want to thank you for taking the time to share your insights today. We at the ABA very much appreciate Land Gorilla’s commitment and contribution to the banking industry. One last question as we wrap up: How can someone get in contact with you for more information?

Sean Faries: Great question. You can go to our website, landgorilla.com, and there’s a I’m sure there’s a lot of different widgets on that website where you can click on and get in touch with somebody here. Also, I’m available on LinkedIn: Sean Faries Land Gorilla. If you just search Land Gorilla and Sean, I’m sure I’ll pop up. I’ll probably respond back the same day, too, if you reach out. So either of those methods are great to get a hold of us.

Tim Pannell: Okay, that’s great. Thank you again, Sean. We also have more about how Land Gorilla can support the business needs of your bank at aba.com. Click on Experts and Peers and then select ABA Partner Network to search the directory. This is the ABA Partner Network Podcast. My name is Tim Pannell, and thanks for listening.