How Could Gig Work and Automation Lead to More Mortgage Fraud? – CoreLogic

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Instances of mortgage fraud have remained relatively stable in recent years. In the second quarter of 2023, CoreLogic estimates that 1 in 134 applications contained fraud, up from 1 in 131 during the same period in 2022. But that doesn’t mean that lenders shouldn’t be on the lookout for warning signs.
In CoreLogic’s 2023 Mortgage Fraud Report, our company’s experts found that suspected occupancy loans nearly tripled since 2020. This type of fraud, which is difficult to spot during origination, typically occurs when someone identifies an investment property as a primary residence to obtain more favorable mortgage rates. Not only does this subcategory of fraud require more attention, but the changing economy and increasing automation brings unique challenges to the mortgage industry.
In this episode, host Maiclaire Bolton Smith sits down with Bridget Berg, a senior leader in loan solutions at CoreLogic, to talk about who ends up paying when someone defaults on a loan and how automation may open the door for increased fraud.
0:53 – Who ends up paying when someone defaults on a loan where fraud is detected, and what happens to lenders that have to buy back loans?
4:10 – Does the normalization of automated underwriting have the potential to lead to more mortgage fraud?
6:30 – Are cash-based borrowers without traditional credit histories turning mortgage fraud into more of a concern?
9:07 – Erika Stanley gives an overview of natural disaster headlines from CoreLogic’s Hazard HQ Command Central
10:58 – What does the future of fraud risk look like?
Up Next
Bridget Berg:
It’s like, “Oh, I don’t make enough money at my regular job. I’m going to hide that and make it look like I have a more of a gig job or that I supplement it.” I don’t think that the people with those sources of incomes are inherently higher risk of fraud, but they open up a pathway that I think others will take.
Erika Stanley:
Welcome back to part two of our conversation about fraud risk across the U.S. In this episode, our host, Maiclaire, will continue talking to CoreLogic Senior Leader, Bridget Berg, about who ends up paying when someone defaults on a loan and how automation may open the door for increased fraud. If you missed part one, I do recommend going back and catching up on last week’s episode where we talked about what fraud is, where it happens, and why latent fraud is difficult to detect.
Maiclaire Bolton Smith:
Okay. I want to shift gears a little bit here because we’ve been talking a lot about fraud and areas where it can pop up, but I guess one of the real questions that I have is who ends up paying when someone defaults on a loan?
BB:
That’s a great question. So most loan sale agreements, so there’s contracts between the lender and the person they’re selling the loan to. They have what we call rep and warrants in those contracts, and one of those representations that you usually make when you’re selling a loan is that, hey, the loan is free from misrepresentation.
MBS:
Okay.
BB:
And then there’s a remedy in that contract that says, “Oh, well, if it’s not free from misrepresentation, we can come back and we can either go after damages or we can make you buy that loan back.”
BB:
So while there’s pages and pages of reps and warrants that are in those contracts, but a lot of them have time limits. Fraud does not have a time limit. There is a unlimited lifetime warranty on fraud. So there’s also no other requirements. So there’s not a requirement that says, “Oh, it has to be the reason the loan defaulted,” or, “It has to actually happened to be a default.” If they find a fraud, they can usually start going after that warranty. So they can…
MBS:
Interesting.
BB:
… make you buy that loan back. Or if it goes to a loss, sometimes they say, “Well, we’ll wait and see how much the loss is. We’ll keep the loan until we know, and then send you a bill.”
MBS:
Oh.
BB:
Either one of those things, on that first one, if I had 10 loans that I found and I pushed them all back to a lender, and say the average loan amount is $350,000, that’s all of a sudden $3.5 million that this lender has to come up with. And they don’t have that money, it puts lenders out of business.
MBS:
Yeah. Definitely.
BB:
When a lender goes out of business, everybody around that lender loses.
MBS:
Yeah.
BB:
Right?
MBS:
Definitely. Wow.
BB:
Or if that lender’s out of business and somebody else comes back to them for the next loan, well, they’re not going to be able to get a recovery and it’s going to go fall back to the investor. So anyway, it hits the investor, and then they kind of domino back through everybody who may have made a rep on that loan as it got sold.
MBS:
Yeah.
BB:
It’s supposed to be built into the pricing on the loan, the piece of the risk, but it’s something that doesn’t happen every day. Kind of like a fire on your homeowners insurance, it doesn’t happen every day. And so it kind of has uneven impacts when it does hit. Even though it might be priced in, it’s going to hit certain people much harder than others.
MBS:
Yeah. So interesting. The other thing that comes to mind is we talked a lot on this podcast about innovation and automation and really how the pandemic sped that up from many perspectives. I know automated underwriting is becoming more common. Is this leading to more fraud, or are there other innovations that are coming in the market that potentially are opening the door to more fraud risk?
BB:
I think it’s both ways. In some ways, the more networking that we do, the more times you can get a direct source, a direct trusted source to validate information. Sometimes the direct sources, they’re not bulletproof. There’s other things that people can do with the direct source, and that might happen in the future where people are figuring out more creative ways to infiltrate, like file a false set of tax returns so that when you go back to pull them. That happens sometimes, but it’s not really necessary. They usually go now to the off-grid sources, like, oh, they don’t have a trusted source when I’m validating a lease, for example. So they go with the simple, paper-based things. So there’s still plenty of opportunities for people to do that.
MBS:
Okay.
BB:
But right now, those trusted sources are pretty good. So that’s a positive that we have more of those. The negative is that everything’s getting more siloed. So that underwriter who’s looking at the whole picture, a lot of those pieces of the picture have been taken away from the underwriter. You’re not spending as much time thinking about that loan. So that opens up the door to other types of control gaps.
MBS:
Sure. Yeah.
BB:
So I think as we see all of the generative AI and the ability to make really, really good deep fakes of everything, we haven’t seen it yet. Maybe they’re so good nobody’s detected it, or maybe it just hasn’t been necessary. So I see both of those things converging. And I think that we need to mature as an industry and figure out, hey, there’s some things we can do in a granular way and there’s some things that we have to do more holistically, and we have to capture more of the data so that we can do it efficiently.
MBS:
Right. Yeah. It’s so interesting. It’s so interesting. And you triggered a thought too. We did a podcast recently on tech in mortgage origination with Praveen Chandramohan back in July, and he talked a little bit about different income sources. At the end, we were talking about people who had a lot of cash but didn’t necessarily have credit because of the way their income came in. And you mentioned a little bit about income fraud. So that got me thinking too about in this current state of — there’s a ton of people who have a lot of cash flow that are coming, whether they’re freelancers or self-employed, that may not have that traditional nine-to-five job. Is that making it more difficult for people like that to get a mortgage that maybe don’t have a credit rating at all or a good credit rating because they haven’t established themself in a certain way because they are just based on cash flow? And do we, I guess the continuation of that is, do we anticipate more fraud potential because we’re starting to see more and more of those people come into the housing market?
BB:
So to the extent that it normalizes it and that people get more used to seeing those off-grid sources, they’ve always been there. There’s always been things that you can’t verify. And so the people who have things that can’t be verified sometimes will hitch a ride on that other train there where it’s like, “Oh, I don’t make enough money at my regular job. I’m going to hide that and make it look like I have more of a gig job or that I supplement it.” I don’t think that the people with those sources of incomes are inherently higher risk of fraud, but they open up a pathway that I think others will take.
MBS:
Interesting. Okay.
BB:
Now, we need to figure out safe ways to serve that. The world is changing. Not everybody’s working for IBM or Apple with a W2, and we need to figure out the safe ways to do that. But at the same time, it does open up a place, a pathway, for people to exploit things to use that, use those avenues that we’re trying to pursue with the cash flow underwriting.
MBS:
Yeah.
BB:
So we have to be mindful of that and think about that as we’re putting those controls in place, but we need to also have some balance so we don’t let it frighten us off from serving people.
ES:
Before we finish this episode, let’s take a break and talk about what’s happening in the world of natural disasters this season. CoreLogic’s Hazard HQ Command Central reports on natural catastrophes and extreme weather events across the world. A link to their coverage is in the show notes.
Hurricane season has passed the midpoint, but that doesn’t mean we’re out of the woods. In fact, Sept. 27 marked the one-year anniversary of Hurricane Ian, which listeners will remember made landfall in southwest Florida as a category four hurricane. One of the key lessons learned from Ian was the effectiveness of building codes and elevating homes. This helps to mitigate wind and flood damage. But as people continue to move and build along the coastline, there is a high potential for another $50 billion insured loss event.
This September though, things aren’t as dramatic. Mid-September has brought Ophelia, the 15th named storm of the season, which hit Emerald Isle, North Carolina with wind gusts of nearly 70 miles per hour, according to the National Weather Service. It was just shy of hurricane strength. Following this storm, Philippe and Rina began brewing in the Atlantic.
Outside of hurricanes, wildfires have been a continual topic of discussion on this podcast. Wildfire mitigation that reduces property risk is receiving increased attention across the western U.S., and CoreLogic is dedicated to helping homeowners and insurers make properties less susceptible to flames by encouraging individual property mitigation and a comprehensive understanding of risk with the Wildfire Risk Score.
In the U.S., the 10 warmest years on record have all occurred since 2010. New research from CoreLogic has found that ZIP codes that have had at least one 104-degree Fahrenheit day since 2000 are more impacted by severe convective storms and cyclones. Inland flooding risk also jumps in these areas. To learn more, a link to the white paper is in the show notes. And that’s the Natural Disaster Digest.
MBS:
So just to wrap up today, I think if we look at what does the future of fraud risk look like? Maybe not do we think fraud’s going to become more prevalent. I mean, I think that definitely we’ve seen is tied to the number of mortgages being written as well, but more on the line of do we think it’s going to become easier to identify fraud risk and potentially stop it from happening as much?
BB:
I think we’ve done the easy things. Most of those things have pretty good controls. But I think everything is changing. We are on the cusp of lots and lots of change, and so the future of fraud risk is really dependent on the ability of our industry to keep in touch with all those changes around us in a constructive way. Relying on underwriters to spot red flags from outdated checklists is not going to do it. That’s not going to help. Or assuming that we’ve totally solved everything through automation is also going to leave us vulnerable.
I think the way forward, and I hope that we can help the industry get there, is embedding, where possible, those little granular ways to identify things that don’t add up. But then in preventing it within the process, during the process, but I think you have to couple that with more data-based oversights at the loan and pipeline levels to identify some of those anomalies that we could see through the metadata.
MBS:
Yeah. Wow. So interesting, Bridget. Thank you so much for joining me today on Core Conversations, a CoreLogic podcast.
BB:
Well, thanks for having me. It was fun. It was really fun.
MBS:
It was. It was great to chat. And thank you for listening. I hope you’ve enjoyed our latest episode. Please remember to leave us a review and let us know your thoughts, and subscribe wherever you get your podcast to be notified when new episodes are released.
And thanks to the team for helping bring this podcast to life. Producer Jessi Devenyns; editor and sound engineer, Romie Aromin; our facts guru, Erika Stanley; and social media duo, Sarah Buck and Makaila Brooks. Tune in next time for another Core Conversation.
ES:
You still there? Well, thanks for sticking around. Are you curious to know a little bit more about our guest today? Well, Bridget Berg is a Senior Leader in Loan Solutions here at CoreLogic. She began her career in the mortgage industry in 1985 and over the years has investigated and cleaned up many types of mortgage fraud and created fraud risk management programs at multiple large lenders. Today, she focuses on all aspects of helping lenders prevent and manage mortgage fraud risk using big data and the CoreLogic Mortgage Fraud Consortium shared intelligence. You can read her industry analysis, including a quarterly mortgage fraud brief, on the CoreLogic website. The link is in the show notes.
©2023 CoreLogic, Inc. All rights reserved. The CoreLogic statements and information in this blog post may not be reproduced or used in any form without express written permission. While all the CoreLogic statements and information are believed to be accurate, CoreLogic makes no representation or warranty as to the completeness or accuracy of the statements and information and assumes no responsibility whatsoever for the information and statements or any reliance thereon. CoreLogic® is the registered trademark of CoreLogic Solutions, LLC.
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