Mortgage servicers must adapt their data strategies to address increasing climate risks. From stronger hurricanes to longer wildfire seasons, understanding disaster impacts on property value is crucial.
Tune in to our latest episode of Steward in the Studio with TJ Harrington, where we explore innovative data solutions and the evolving landscape of mortgage servicing. Let’s turn insights into action!
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Speakers for this episode include:
Marvin Stone
As Senior Vice President, Director of Strategic Initiatives for Stewart Lender Services, Marvin Stone is working on the digital transformation of the transaction process for Stewart’s full range of services that cover the entire mortgage lifecycle. He also contributes to industry technology by participating in MBA’s MISMO Title and Settlement Community of Practice and being part of Stewart’s generative AI council.
Stone has been with Stewart since 2007 and has managed various technology, process and compliance initiatives for the direct, agency and centralized title divisions. Before joining Stewart, he was CIO for a large title company on the West Coast and held strategic roles with other national underwriters and mortgage lenders.
Stone is a frequent speaker at industry events and is sought out for his commentary on industry trends.
T.J. Harrington
T.J. Harrington serves Stewart Lender Services (SLS) as Senior Vice President of Sales and Product Enablement. In this role, T.J. focuses on expanding Stewart’s reach and influence in the title, appraisal/valuation and credit/verification industries.
His extensive experience includes serving as general counsel and strategy-focused roles at major lender services and bank-owned mortgage and title operations.
E16: How Data is Transforming Mortgage Servicing Climate Risk Strategies
So, TJ, let’s start with how disasters such as hurricanes, tornadoes, earthquakes, and especially fires are are changing. I pulled some FEMA stats, and they showed tornadoes are more frequent, hurricanes are stronger, and wildfire seasons are not only longer, the fires are burning hotter and spreading faster. So we hear a lot about how these changes impact insurance companies, but how does this affect mortgage?
You know, Marvin, it’s an interesting question. We talk about insurance as being the primary kind of carrier of the risk for property casualty. But what we’ve seen is a beginning of an evolution in both the shopping process, loans in flight and servicing related to disaster risk, where home buyers are now much more aware of how disaster risk plays into the value of a property, whether it be from resale purposes, whether it be risk of casualty, or as you mentioned, impacting the affordability or even the availability of, insurance coverage. So we’ve begun to see data points around, shopping tools that say, hey, this home is or is not in a flood zone. This home is or is not subject to earthquake risk. This home has a higher than average fire risk. We’ve begun to see those kinds of stats working their way into savvy, consumers’ hands during the shopping experience.
We’ve also seen just kind of a traditional process of loans in flight where you’re in a scenario where a loan is closing or is in rescission for the case of refi or or HELOCs, where there’s a disaster that hits and lenders are panicked about whether the disasters impacted their home. So today, we’ve seen just a plethora of responses. Most typically, there’s the requirements of home inspections, but we’ve seen some more data-driven offerings there. I shout out to my friend Sarah Costa at Veros.
They have something called disaster vision, which sets a kind of ring fence around disaster and gives you a probability score of whether your subject property is within or without the impact zone of the disaster, which has some really good benefits as far as saving costs for ordering, inspections, or even having drones fly by. We’ve seen the increased use of drones in other places, and we’ve seen some of that technology and those items go into the servicing space, which I think is actually probably where the risk has pooled the most from a disaster perspective.
And it’s a couple different things. Number one, I think servicers are getting savvy to the fact that and investors in particular, people that are buying the MSRs or whole loan assets are saying, I may be buying a pool of loans that have additional risk to them other than the financial risk that I’m modeling. So you see investors going, man, there’s these ZIP codes or geolocated areas along fault lines are subject to tornadoes or hurricanes that maybe an MSR pool is heavy for those loans just based on originations activity or other activity in the market. And so investors are getting savvy to that, and they’re beginning to price their loans accordingly. Another shout out to my friend Tom Piercy from Incenter. Tom is a a a whiz at MSR trades. He’s been in the business for a very, very long time. He is beginning to see some of those data points crop up in MSRs where they’re asking more information about the makeup of the pools from a geography standpoint. And he does think that savvy investors are beginning to price that out, which does, again, flow into servicing, where servicers are boarding these loans and may have additional risks.
So we’re seeing today, with just the GSEs, Fannie, Freddie, and the govies, and even nonconventional, there’s all kinds of reimbursement schemas for disaster. And and what we’re finding are servicers are struggling to be efficient to use those dollars effectively, particularly as these risks have increased. So I think there’s a new playbook forming around products and services to servicers to help them deal with these disasters and whether that be something in the insurance to make sure that insurance coverage is proper and appropriate for the value of the home and the risks posed all the way to the playbook for what happens when disaster hits.
So you talk about this new playbook, and it sounds like data is, you know, at the heart of this new playbook, really having good data and being able to really understand what’s in your portfolio. So a lot of people think of Stewart as a title company, which makes sense. I mean, hundred and thirty years in the business and counting. But we’re also a data company providing millions of data records to, mortgage lenders, servicers, and more every week. Can you explain how data can be leveraged to identify potential risks within a mortgage servicers portfolio? And then I guess the second part of the question is, are there specific indicators servicers should be watching for beyond what you mentioned?
Yeah. So that’s a great question, Marvin. So Stewart’s been acquisitive lately and has combined a number of best in class solutions in the industry, including Informative Research, which is our our CRA and verifications platform that also has a data analytics team attached to it that has done some really wonderful things for originators and servicers and helping them understand, their data usage and their risk profiles of their portfolio.We also are excellent about identifying best in class solutions in the marketplace and partnering, with those solutions. So, again, partnering with Veros, so on Disaster Vision and other providers in the market, to say, “Hey, what can we do to combine data that we generate and possess in Stewart, with other data in the market with the services that we have to really craft solutions?” But you’re absolutely right, data is the tip of the sword. So what we see from a data perspective is disasters tend to be geocoded, but we’ve seen analytic models that have gotten even sharper with topography for flooding, with understanding of the topography and terrain around houses from a fire risk perspective. You know, you’re gonna be less worried about a home next to a river or a wetter part of wetlands versus next to dry grass, next to a forest, next to something that is generating I mean, heck, in California, unfortunately, power lines,right? That seems to be a genesis of some of the fires that we’ve seen. So, really, the idea of understanding the asset risk, but also what counter risks, what compensating factors do you have. So that comes into insurance. So what we’ve seen on the origination side of the house has been not a very good process in reviewing HOI decks for both coverage perspective and and value.
And there’s a partner company called Yolo that we’re working with to build a due diligence product that we’re attaching to Informative Research and other places in Stewart to be able to analyze the contents of the insurance deck at originations to ensure that the insurance policy conforms with the investor guidelines. That’s number one tip of the sword. You know, it’s kind of the preventative medicine up the stream. I think that prevents some issues from a buyback risk in, other places in the origination process.
But also taking that same tool and leveraging it with servicers and saying servicers, here’s a tool that we can run over your portfolio, along with these other data analytics points on the asset to determine actual risk. And the insurance piece has kind of a been a tough topic in the servicing space, namely because there’s been a lot of fights about replacement cost value. You see the GSEs requiring replacement cost value whether their loan balance is above or below that replacement cost value. And at the same time, you have the CFPB saying, hey servicers and subservicers, you need to be really careful about lender placed insurance, about pulling the trigger on that very, very early and making sure that consumers understand that the lender placed insurance only covers the investor and the loan, not content, not possessions, not anything else. Really just trying to get the home back into place to preserve the asset.
And so one of the things that we’ve focused on the last probably six months or so has been finding a company like Yolo that can do the due diligence and then standing up believe it or not, Stewart Title has an insurance division. We have a we have a company that writes property casualty, and specialty insurance, and we are able to produce a policy that conforms to GSE guidelines on replacement cost value, tying in the knowledge we have in the asset and the discipline around insurance where servicers, if you have a situation where your, consumer’s policy has tipped below replacement cost value, Rather than pulling the trigger and going right to lender’s place, there’s this interim step of being able to go to a a marketplace of carriers that we provide to say, hey.
There’s this other option, mister consumer, missus consumer, that does provide content insurance that does protect your assets. And here’s an option to go with this other, insurance before going to the lender’s place. So that’s that’s kind of been what we’ve seen from a compensating control standpoint. But, again, to your point, the data rich environment about the actual topography, about the actual risks, the historic risks, But, you know, it’s causation versus correlation, Marvin.
Past performance doesn’t always equal future activity. Just given the nature of what we’ve seen from a disaster risk, it’s been steadily increasing in both frequency and severity. And so the idea of trying to get ahead of it with, controls and data is really, I think, is really where the future is going for servicers.
Yeah. I look back to, years ago. The insurance question was, is insurance in the file? Do you have do you have insurance in the file? And it was kind of an afterthought. It was kind of a done deal. And from the consumer standpoint as well, now you have insurers, pulling out of key areas, insurers raising the cost, etcetera. You know, Stewart Insurance, they have a real consultative approach that kinda walks you through these things.
I’ve been buying insurance for years, and it just kinda reminds me that we really aren’t experts on this thing that we do once a year. And I’m sure that, you know, servicers are dealing with that when they have these conversations with homeowners, so it’s pretty challenging.
You’re absolutely right. And the challenge too, Marvin, is that right now, in some in some scenarios, lender placed insurance is more affordable than a full coverage policy. So because the coverage is so skinny and that’s been the dynamic that we’ve seen. And that’s a challenge, right? And that and that, I think, does lead to potential regulatory issues. I think it leads to potential lawsuits, which is really my concern from a servicer’s perspective where they’re trying to do the right thing by both the investors and the consumers in servicing the loan. And, ultimately, should a disaster happen and a consumer find themselves uninsured or underinsured based on having lenders placed, I think that leads to potential litigation, which is really why the consultative approach of the Stewart Insurance Group and having them brought in in in a conjunction with a portfolio analysis from IR really does make sense for servicers to really look at that risk in a way and change up their approach with consumers.
Interesting. So, okay. So, TJ, it’s twenty twenty five, and that means there’s something that we are required to do. We’re required to do it, and that is to bring AI into the discussion. So AI is always in the news, every single day, all day long. What role does technology such as artificial intelligence or, you know, even just advanced analytics play in turning raw data into actionable insights?
You know, Marvin, I think that’s still a like much of AI, there’s a huge amount of promise there, and I think a lot of the use cases are still being flushed out. So I think that AI is able to take all of the datasets produced by the folks that are generating the really great topography fire risk, all all the risk factors that we’ve identified and and have tied to actually correlated to loss and able to build a risk profile on a property. I think we’re getting to that point with AI. I think the issue is really with all AI, it needs data. It needs to be fed, and the models need to be sharpened. But I think we’re getting there. I think at some point in the not too distant future, we’ll be able to run an AI tool over a whole portfolio, really say, this is where we should be looking at additional risk. And a lot of it too is triaging the risk factor.
So we’ve seen AI models begin to emerge in hurricanes and and predictors. I don’t know about you, but when I was a kid, I remember just seeing one hurricane path. And now you go to the weather channel, and you see twelve different squiggly lines that represent different models. And AI is being deployed to begin to coalesce those models and create more accuracy. And I think we’ll see the same thing.
You know, the name of the game today, though, still in the disaster playbook is triaging the risk and getting boots on the ground or some sort of, good intelligence. And that could be anything from contacting a consumer to flying drones over the area and identifying, the the property condition to having boots on the ground inspectors actually look at the home. And I’ll tell you that the use of drones in AI has become prevalent to the point where through computer vision and other tools that we have in SVI, we actually can identify the the property and and spot any defects. So that’s something that we do deploy today for property condition gathering, flying a drone over, taking some snapshots, and going, man, that looks like the roofs came in. That looks like this has happened. That looks like this kind of water damage. Now we’re getting to that point where, eventually, we’ll be able to obviate the need for boots on the ground.
But today, you know, the best practice is still putting the inspectors on there. But the idea of something like Disaster Vision from bureaus that we’re who we partner with on the resale of that product, that gives you the chance of, hey, let me stack rank my resources. Let me go to the who needs the help the fastest and the most desperate and have that help, come early, get that process for insurance started, get any relief effort in there started. So the the idea of AI right now is an enabling and predictive tool. But in the long term, you know, it really can be the end all be all.
So, historically, you know, the the disaster response has been sort of a blanket to blanket the area, from a servicer standpoint. But, you know, maybe going beyond regions or ZIP codes, you’ve talked about topography and kinda drilling down deep. What is that what does that look like?
Yeah. It’s laying the data over your portfolio, looking at the address, seeing where it hits from a from a geo perspective and the topography and being we this was that’s something we saw in North Carolina and the floods out to the to the west of me and from Charlotte, where we had properties where the whole county really was was just flooded.
But what you had was some high ground properties that weren’t impacted. So you had some middle ground properties that could have been impacted just based on where they were from an elevation perspective. But because of the the channels and the valleys, they were out of harm’s way. And then you had massive properties that maybe were higher up, but fell along the path of water as it flowed from the high, elevations down to down to the valleys.
And really, the response could have been triaged based on those factors with some really great data that we now possess. The challenge today, and I really throw this kind of gauntlet down at the feet of the GSEs and FHA and VA. Today, the way that reimbursement structures work is if there’s a disaster in your properties in the ZIP code and you have to carry out certain activities to mitigate, you’re reimbursed for your cost for that. That’s part of part and parcel of servicing.
And so the reimbursement structure is here’s a check for reimbursement, and it’s not based on, there’s no incentivization to spend on other products to kind of shape the disaster response today. So that we see less of that in the servicing space, and I think servicers do crave for something to be able to be more efficient, not just throwing bodies and call banks and and reaching out to consumers, but really having actionable intelligence around it. But today, again, in the servicing space, that’s not what’s always happening because the incentivization from a to aligned to the seller servicer guideline, aligned to the, program guidelines are just not structured that way.
Interesting. So how can data services, like the data services we provide through Informative research or through our partner network, help servicers stay compliant on both a federal level and with state regs while still managing their risk exposure?
So I’m a big fan of being proactive with solutions. I really do think that the tip of the sword for risk assessment should be at the due diligence stage and at the loan onboarding stage. We should have a full picture of what’s coming in the house, and I don’t know that we’re doing that today. I think that but I think those are overlays that we have today and the ability to really provide that data as a uniform set to be consumed and assessed. I think knowing what you’re putting into your servicing book from a risk perspective, the the future of servicing as we drive to more efficiencies is really going to be about identifying the risk before it happens and being able to plan accordingly. And so I do think that the dataset and the compliance pieces, I think they’re all there today, Marvin, because the world is not yet built for the regulations and the compliance structure is not built for the world that we’ve we’re in now and are headed to where, you know, it used to be that disasters were black swans, and now we have a flock of black swans with the type of disasters that we’re having. Shout out to my friend Eric Lappin who likes to throw in, music references. So flock of seagulls, flock of swans.
That’s three shout outs. That’s three shout outs.
I’m I’m hitting my max for shout outs in Stewart in the Studio.
But the idea that, the regulatory there’s definitely administrative pieces. I I know today that disaster data for FHA and VA go directly to the White House, and there’s a there’s a climate change disaster response kind of team around that tied to the executive branch that are really, really savvy to what’s going on. But those things have not made it into seller service guideline. They’ve not made it into policy at FHA and VA.
And so we’re still behind the ball from a reality perspective, which then, unfortunately, servicers and subservicers are tied directly to that. Right? Their their action and playbook is really tied to their requirements, and it’s hard for them to get ahead of it because if they get ahead of it, they’re probably not being reimbursed for it. And so the idea that we have these datasets and items that are available and actionable would have to be tied to cost savings, have to be tied to making them more efficient, have to be tied to expenses they may be incurring outside of what’s reimbursable. So the idea that we can save on staffing, that we can triage responses and and be efficient, I think that’s where we’re looking, Marvin, just from from a today perspective. And the challenge is really from, our stakeholders upstream in the stream in the process that maybe hold a little bit more responsibility for the rules to take a hard look and say, what can they do? You see it in their goals. You see it in the policies saying, hey.
We’re gonna be, ready for these items, but we haven’t seen real action on it yet. So it’s a call to action to help servicers be able to be as efficient as they wanna be in consuming these solutions and changing the reimbursement structures.
Good. So I was gonna ask you about being proactive. You’ve done a lot of research in this area. We have, what, three or four different solutions across Stewart and the partner network that, would be of interest to servicers. The call to action really is just get with you, kind of explore what’s available and what’s coming so that servicers can plan their approach.
Yeah. Absolutely, Marvin. I think the tip of the sword really is the insurance solution both at originations and on the portfolio analysis, and particularly as renewals come up, and as issues arise regarding the availability and coverage of replacement cost value, partnering with the Stewart Insurance Group to be able to produce policies that are an alternative to lender placed insurance. I think those are actionable today and solve a problem that’s in the servicing world today.
And I think, honestly, as we begin to evolve kind of the portfolio review solution and deploy more of the, Informative Research Data Solutions with Shannon Santos, we can absolutely layer in the climate data and package those as a value added solution. That’s something that we’re we’re looking at and definitely, looking forward to chatting with servicers. I, you know, I had a very nice conversation with the nation’s largest subservicer a couple weeks ago on these issues, and and they feel the pain of it and are looking for ways to be better. Again, they’re handcuffed a little bit, and they’re looking for some relief. But, definitely, we’re at MBA Servicing in a couple weeks, we’ll be there with the whole team to be able to talk about these things, and, definitely looking forward to catching up with everybody. This has been a topic, Marvin, that we’ve been kicking around for probably, two years.
And I feel a little ghoulish that the topic is now so pertinent now with what happened at the end of the year and what’s happening now in, the western part of our country when the fires in LA. But, really, it’s been a risk, and we’re just now having bad dice rolls, and it and the and it’s happening. And it’s in advance of NBA servicing where it’s topical. And I think that there’s some things that we can do or act that are actionable that will make the world better, and we’re continuing to build a solution to Stewart.
Need better data to cope with stronger hurricanes, massive floods, devastating tornadoes, and raging wildfires? Meet with TJ Harrington and the Stewart team at MBA Servicing at the Hyatt Regency Dallas coming up this February fourth through seventh.
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