A Conversation with Matt Karli
In the real estate economy, we all know the old adage “location, location, location,” but location matters for far more than just determining the market value of a home, and the science of finding the answer of where that home is located is a lot more involved than meets the eye. Is it behind the Whole Foods? Is it halfway down the street, at a specific pair of coordinates, or where the building sits on the land?
In this episode, host Maiclaire Bolton Smith talks to geospatial and location expert Matt Karli. He unravels the complicated question of “where?”–and reveals how location intelligence can even save lives.
Maiclaire Bolton Smith: Welcome back to Core Conversations, a CoreLogic podcast. I am your host, Maiclaire Bolton Smith, and I’m the Senior Leader of Research and Content Strategy with CoreLogic. In this podcast, we’ll have conversations with industry experts about key topics, from housing affordability, to the impacts of natural disasters on property.
When talking about real estate, we always hear the phrase, “location, location, location,” as the number one factor determining the value and attractiveness of a property. But where something is located actually underpins the entirety of the housing economy. The general location of a beautiful waterfront mansion will tell us that the home has a high market value, but getting the placement of the building on the parcel of land just right can determine for a lender whether or not a homeowner has to buy flood insurance. And the precise distance from foliage can tell an insurance company how likely the house is to catch fire.
Sometimes knowledge of location can even save lives. Knowing precisely where a pipeline is before breaking ground can mean the difference between injuries and a beautiful new development. So for our episode today, we’re going to dive into location intelligence with one of CoreLogic’s experts, Matt Karli, who leads the team responsible for the CoreLogic geospatial property and location intelligence product portfolio.
Matt, welcome to Core Conversations.
Matt Karli: Hey, Maiclaire, thanks for having me on the pod today. It’s great to be with you.
MBS: Awesome. Okay. So to get us started today, can you tell our listeners a little bit about your background and your role here at CoreLogic?
MK: Absolutely. So I have been with CoreLogic for over 20 years, and I’ve been in a variety of roles in that time. But what’s interesting about them is they’re all, and each and every one of them, has been rooted in property location and location intelligence in some way, whether it was being responsible for actually performing flood zone determinations and looking up individual properties or managing the teams associated with that, or building out large scale nationwide property level, geospatial, datasets. In some way or another, I’ve always been involved in property level location intelligence.
MBS: That’s really cool. So I’m glad to have you here today. And just to start off the top, can you explain what we mean when you say location intelligence? Can you define that for our listeners?
MK: Yeah, and it’s a great question to start with because location intelligence can be really broadly defined. So if I can give it a shot, it all has to do, and it all comes into play whenever you’re talking about data elements. And those elements could be anything. It doesn’t matter what they are. And you’re applying some sort of geographic or mapping component to them. You want to know where they are in the physical world. At the end of the day, what you’re trying to understand is how these elements relate to the place that they are in the physical world, and all the things that are in their immediate vicinity. And you’re stepping into the role of location intelligence when you’re thinking about it that way.
A perfect example of this that I can point you to is a question that I actually asked you yesterday, Maiclaire. And there’s a long story about why I asked you that question, but it had to do with the address of the old CoreLogic Austin office. CoreLogic moved their Austin office about two years ago. And I asked you for the address, and the answer you gave me was absolutely a perfect example of location intelligence, because you said it’s the office building behind the Whole Foods. And while that isn’t the address that I was looking for, it was an absolutely amazing example, because the location of that office is grounded in its proximity to the Whole Foods. And that’s how you think about it.
MBS: Exactly where it is.
MK: That’s right. Well, there’s La Quinta between the office and the Whole Foods, but close enough. But that gets to the point. You’re comparing something that you can know and relate to on the earth and saying whatever I am interested in is in proximity to that thing.
So when you’re thinking about advanced location intelligence, you’re generally talking about utilizing big data sets and oftentimes complex and multifaceted data sets to sort out the complex relationships that exist between different data elements. And there’s no way to arrive at an exhaustive list of what those data sets might be. It’s really going to be completely dependent on what question you’re trying to answer, or what you’re trying to get insight into. And there’s also a very, very heavy software and hardware component to it that you’ve got to really think about to really get to large scale, deep learning, deep analytical location intelligence.
MBS: First of all, I had no idea that you were testing me, and I’m glad I gave you an informative answer. And my first response was, you worked in that office for 20 years. Why are you asking me where it was?
MK: I knew exactly what the address was.
MBS: I’m sure you did, but no, that was fantastic. I love that example, and it’s such a perfect way to get us started. So, who uses this kind of information? All of us know relatively where buildings are, but is it relevant if we’re looking at from a homeowner or a business, who would use this information, and if we looked at businesses specifically, what kind of businesses would use location intelligence information?
MK: Well, I know that you’ve heard me say this before, Maiclaire, but our listeners probably haven’t, that everything is spatial. Like in my world, I view everything is having a spatial component. And so, absolutely homeowners are going to be interested in a location component, a spatial component. Businesses are obviously going to be interested in a spatial component. I’m often of the mindset, and I know you’ve heard me say this before too, that if businesses aren’t thinking about their assets, their infrastructure, their product portfolio in a spatial manner, they’re really potentially being left behind and they’re missing a key component of insights into their customers, into their assets, into their infrastructure, that is really going to be important for developing and growing their business in a way that really makes sense for their customer.
MBS: Okay. So if we look at CoreLogic, and you’ve been doing this more than half your life, and when we look at CoreLogic specifically, are there examples where we’ve provided data on location intelligence that have had a really big impact? Can you give some examples of how this has been really relevant?
MK: Right. So I would say that the biggest area that CoreLogic’s really made a very sizable impact in the area of location intelligence is related to our ability to locate structures and properties at a very, very granular level. If you go back into the early 2000s even, and you think of the world of geocoding. Geocoding was all based on an interpolated street. You were guessing where along a street segment, a particular property was, and anybody who used any sort of mapping application, and during that timeframe, whether it was the late 1990s or the early 2000s, you might remember MapQuest. And you looked up your address in MapQuest to go to a friend’s house and you ended up halfway down the block, or you were lucky if you were halfway down the block. And that’s because it was using utilizing street data to try to arrive at a precise location.
Well, CoreLogic really tried to identify where we could provide deep insights into the precision of a location in a property. And that goes back to our roots in the flood services business that I referenced, was one of my first jobs is performing those flood zone determinations and locating properties at a very granular, very precise level. So, what we really focused on was how can we take that capability that we developed as part of that internal business, and scale it out to other users outside of CoreLogic? And that really is an area that we’ve had a really large impact in.
MBS: So you triggered a thought there, and I want to say on this topic of natural hazards, and you’ve mentioned flood, and I know flood’s a big one. So we talk on this podcast a lot about the impacts that natural hazards do have on property. So when we think of location intelligence, how can we help improve responding to a natural disaster? Especially because many times, time is of the essence.
MK: No, and that’s key. And I’ve said before, we’ve got customers that are in emergency response, they’re in community engagement, they’re responsible for critical infrastructure. And they ask themselves this question all the time. And the most progressive of these companies are asking that far before an event’s going to happen. If you’re responding and you’re trying to make those decisions when an event has happened, you’re way behind the eight ball. You’re going to have a really hard time responding effectively to those events. So, the key thing I would say would preparation, what is the key threats to your infrastructure? How are your infrastructure potentially going to be put at risk by different events? And there’s lots of different things you can consult as part of that, as a focus on the area of location intelligence, where are the high risk areas?
You’re very familiar with the natural hazard risk areas, where are those areas of high, medium, and lower risk? What is there, from a perspective of whether you’re managing infrastructure, whether you’re managing your own assets or you’re a community responder? What’s there, is it a bunch of single family residences? Is it a school? Is it a hospital? Is it a fire station that might be potentially damaged by this, and take out an entire fire department? Those are key questions you need to start asking yourself, regardless of your position, whether you’re a community leader or whether you’re in business. What of your critical infrastructure is going to be impacted by any potential event, and how do you plan for that, and mitigate around it?
MBS: No, and I’m so glad you got into that, because the topic of resilience and really preparing for a disaster before it happens is one that’s really important to me. And it’s something that we’ve talked about a lot on this podcast before too. And I think you’re really getting into that. And I know myself and many of the people that we work with, important parts of our careers, are we so passionate about helping people. And I think you’ve given some examples of how location intelligence can help protect or help people. Off the top, I used the example specifically of, you have this beautiful home by the river, does that home need flood insurance? And knowing exactly where the property is, and the location intelligence, can really help you understand, is that in a flood plain? Do you need flood insurance?
If you can see a river, you need flood insurance is my personal view. But it can give you a better understanding. And from an insurance company perspective too, it can give you an understanding if you were underwriting a home that is of risk, for both wildfire, if you’re near trees and a lot of brush stones, or if you’re near water, and potentially a flood zone. So can you talk a little bit just because you’ve had so much experience with the flood zone determination stuff specifically, can you talk a little bit about that and how that works and why it’s so important?
MK: And no, it’s a fantastic question, because it’s a thing that no one thinks about. And your example of if you can see a river, you probably need flood insurance. I would take it one step further. I remember in my time in the flood zone determination business, one of the things you do is you’re performing the flood zone determinations for somebody whose mortgage to be underwritten. And if you determined that they’re in a flood zone, there’s a process where they can come by and say, “We think you’re wrong. We think that you’re not correct about that.” And that’s called the dispute process. We’ll essentially redo the determination. We’ll help them through any sort of map amendment process that might be necessary.
But I remember one example, and it sticks in my mind 20 years later, where a customer came back and they submitted a hand-drawn sketch of their property. And it where the house was, where it was on the property, and at the back of the property, they said, “Here’s the house, and then here’s the dry creek.” And it said this creek is dry until it rains. And that’s exactly right. And they’re probably exactly right. There probably is no water in that creek, until it rains. But the fact of when it rains, the map has shown that it’s going to impact that structure and place them in a flood zone in a high level of flood risk.
Flood is one of those things that no one thinks about until it’s happening. And that’s the reason that FEMA exists and the NFIP exists. And it has that requirement for mortgage companies to require flood insurance, when the house is at a high level of risk. Now, it’s not perfect. That’s the reason we have some other products that augment that, for insurance companies and mortgage companies alike. But it’s important that people have knowledge that that risk is there. And it’s not always apparent, because the creek is dry.
MBS: Right. And I’m going to do a little acronym check here. You did mention NFIP, which is the National Flood Insurance Program. I want to talk about that a little bit too, because a lot of people, to get a mortgage, if you are in a determined flood zone, as defined by FEMA, then you’re required to get flood insurance under the NFIP. But those are not the only areas that can flood. And I think that that’s something that people need to consider as well too. And that’s part of knowing your risk and having an accurate representation of where your property is, and understanding that what your risk actually could be.
MK: Yep, that’s exactly right. Because again, the FEMA Special Flood Hazard Area is defined by a line on a map. And I know, and many others know, that the flood waters are not bound by that line on a map. They do not respect it for some reason. And so, it isn’t necessarily a true representation of your overall risk of a flood. Just like any other risk map, isn’t necessarily a representation of any particular level of risk for any event.
MBS: Yeah. It’s not binary, it’s not risk or not risk.
MK: Correct. It’s not a yes, no. Exactly. It’s a continuum.
MBS: There’s levels of risk. And those waterfront homes are the ones that are the most desirable. That’s where everybody wants to live. So understanding where your risk is. So, okay. So if we think about the risk and the importance of location intelligence, for things that are not related to natural hazards, what are some examples of where location intelligence is relevant or important?
MK: No, that’s a fantastic question, because it’s not limited to natural hazard. We serve a lot of industries that aren’t dealing with natural hazard at all. They’re dealing with fleet management, or they’re dealing with infrastructure management, whether that be power lines, communication lines, whether it’s long haul cable or 5G towers, or something like that. They need to understand, what does that infrastructure near? What’s potentially putting it at risk? You think about vegetation management for the utility companies. One of the things that we know from the storms in Texas is obviously there was a lot going on in the winter storm in Texas, in February 2021. But one of the things that we know was an impact, outside of the generation problems, was power lines were being impacted by downed trees, downed limbs, things like that.
And one of the things utilities, and utility customers know this very well, utilities know that they’ve got to manage this, it’s called vegetation management. And they’ve got to go in, they’ve got to keep the trees and the brush and whatever might be growing around those utility lines away from them so that they don’t fail catastrophic. So they don’t have outages, or at least that they’re limited and can be dealt with quickly. And if you don’t appropriately manage your vegetation, you’re not going to know that. Well, understanding where your lines are, what’s near them, is going to impact your efficiency as it relates to that vegetation management program.
And the central Texas area is a good example. I’m from central Texas, so I can speak to that really, really well. If you go east of Interstate 35, it’s relatively flat land, there’s not near as many trees, and everything like that. As you move west of Interstate 35 in the Austin area, there’s a lot more trees, there’s a lot more brush, it’s a lot more hilly terrain. And all of that impacts how efficient you’re going to be in managing your vegetation. You’re probably going to have to go trim more frequently. It’s going to put your crews at more risk. And so you’ve got to consider that, and that allows those users to manage that effectively.
MBS: And you used an example in Austin, but I think every one of us can just think of where we live and think of similar examples of where there’s vegetation and where there’s terrain, and it’s not unique to a particular city. This happens everywhere. We talked a lot about the impacts on homeowners and businesses. I know you do a lot of work in the utility space as well too. Are there any examples that you can share that where location intelligence has been really relevant and important?
MK: Well, so one of the areas that always sticks out to me is it’s not just what’s on the ground now that you’ve got to consider. It’s what was there before, and what could be there in the future. An example that I always like to think of is if Rancher Anderson has a parcel, and he’s adjacent to a pipeline that my oil and gas company put in the ground 10 years ago, let’s say 2005, they put an oil and gas pipeline in, and it’s open ranch land. There’s nothing around, so the oil and gas company is not too concerned about that.
Well, Mr. Anderson sells his ranch to a farm, and they develop Anderson ranch subdivision. That is a multi-use subdivision. It’s got 150 single-family residences. It’s got a commercial area with a Starbucks and a bookstore and whatnot, a couple of restaurants. And there’s plans in 2022 to add an elementary school. Well, if I’m an oil and gas company, and I’m operating that pipeline, I’m responsible for that maintenance of that pipeline. I care very deeply where those homes are, where that commercial center is, and where that school is planning is going to be, because it’s going to impact how I decide to operate my pipeline, or how I’m actually allowed to operate that pipeline based on state and federal and regulations. And so understanding how that property went from empty ranch land to now it’s a single-family, residential subdivision with a business unit and a school. All of a sudden that changes how I perceive things that are going, and it’s going to impact how I operate with everything around that particular pipeline.
MBS: Wow. No, super, super interesting and really relevant and important, and probably something that doesn’t necessarily cross everybody’s mind on a regular basis. And this is something that’s foundational in absolutely everything that we do. And I think that’s what we wanted to highlight from this podcast topic is that we don’t necessarily think about how this is something that is so relevant. It’s one of those things that when it goes right, we forget about it. We don’t even think about it. But when it goes wrong, then it’s a big deal.
So, okay. So whenever we wrap up these podcasts, I like to think about if we were to look into a crystal ball and we looked to the future, what do you think the future holds for location intelligence? Technology is all around us. Everything is innovating all around us. How does technology play a role in the future of location intelligence?
MK: Well, first of all, I want to be 100% clear. I absolutely do not have a crystal ball, because I wouldn’t be working here if I did. I’d be doing something else, probably a lot more fun. But as far as the future of location intelligence is, I think we’ve obviously are going to continue to see advancements on the hardware and software side. That’s never going to end. We’ve seen huge advances in those areas and it’s bringing really strong insights and a lot of power to really do a lot of analytical crunching. The other thing that I think we’re going to see, and I expect to see, and I hope to be part of it, because it’s what I’m focused on, is bringing more granular and more detailed location information to drive the necessary decisions that all manner of users have from a wide variety of data sets.
Whether they’re property location data sets or not, I think that having that detailed and granular information is going to be very important. And then the key thing that I always focus on with any new data asset, and I encourage my customers, I encourage my employees, I encourage everybody that I interact with to think about it this way, is think about the particulars around those data, sets themselves. How it’s collected? How is it validated? How truly accurate is it?
Because not all data can be treated equally, nor should it be treated equally. And the saying “garbage in, garbage out” is never truer than when you’re talking about data. If you don’t have the most accurate data, you’re not going to be able to make good decisions and good insights. And that’s why we’re always focused here at CoreLogic on ensuring that our data is the highest quality, not just for our customers, but also somewhat selfishly because we rely on our own data ourselves for so many of our different business operations. That we recognize what’s at stake, if you’re making a decision off of bad data.
MBS: Well, I’m glad you ended there. Because I think that’s just so important as we do often hear “garbage in, garbage out”, but it’s really relevant, and it’s really important. And the quality of data is just of the utmost importance when we’re dealing with just about everything that we do these days. And the only thing I don’t agree with you on Matt, is how could you find something more fun than this? This is the fun.
MK: It is a good time. It is a good time.
MBS: Well, this has been so great to have you here today on Core Conversations, Matt. Thank you so much for joining me.
MK: Absolutely. It was a pleasure, Maiclaire. Anytime.
MBS: All right. Well, we might have to have you back, because I think you’re going to be a fan favorite. You’re a fun guest to have.
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