IN PARTNERSHIP WITH ATTOM DATA SOLUTIONS
FEBRUARY 2019 VOL 13 ISSUE 2 THINKREALTY.COM/HNR
Data-Fed Disruption Bringing Balance to the Mortgage Marketplace
MY TAKE IBUYER GROWTH GROUNDED IN SPEED, SIMPLICITY AND CERTAINTY OF A CASH PURCHASE 16
BIG DATA SANDBOX HOUSING AFFORDABILITY SILVER LININGS 24
MARKET SPOTLIGHT TASTE OF TEXAS 22
Contents
FEATURED ARTICLE
With mortgage rates weakening demand and an increase in mortgage application fraud, the need for data analytics and technology innovation is ramping up. Hear from several industry experts on how a data-driven mortgage marketplace, if properly implemented can ultimately improve both the user experience and reduce risk. 04 DATA-FED DISRUPTION BRINGING BALANCE TO THE MORTGAGE MARKETPLACE
16 MY TAKE: IBUYER GROWTH GROUNDED IN SPEED, SIMPLICITY AND CERTAINTY OF A CASH PURCHASE
Rob Barber, CEO of ATTOM Data Solutions, discusses the evolution of the iBuyer and how their emergence in the marketplace has caused a disruption in traditional real estate transactions. He analyzes the top players in the iBuyer space, those who are just emerging and those who are taking a different spin on the model.
04
With population and job growth heating up in Texas, so is the housing market. This analysis dives into the state’s five largest metro areas: Austin, Dallas, El Paso, Houston and San Antonio to assess real estate investing opportunities. 22 MARKET SPOTLIGHT: TASTE OF TEXAS
16
32 BIG DATA SANDBOX:
HOUSING AFFORDABILITY SILVER LININGS
This infographic shows the results of ATTOM Data Solutions Q4 2018 Home Affordability report and helps to shine a light on those areas where buying a home may not be so out of reach. The analysis looks at median home prices, coupled with average wages and what is needed to make a monthly house payment at the local level.
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U.S. RESIDENTIAL MORTGAGE ORIGINATIONS
PURCHASE
REFINANCE
HELOCs
6,000,000
5,000,000
4,000,000
3,000,000
2,000,000
1,000,000
0
FEATURED ARTICLE
Data-Fed Disruption Bringing Balance to the Mortgage Marketplace
AS THE MARKET TURNS Lilly said that Phoenix recognizes the shifting market and in response is advocating a dual strategy com- bining data-driven efficiencies with strategically applied insight from subject matter experts. “As the mortgage environment aggressively adjusts from scaling to meet customer needs to capturing margin in a severely contracting market, it will be important for all participants to get the most out of each asset,” he said, referring spe- cifically to the MSR space. “A combi- nation of data tools and specialized knowledge will be applied to retained portfolios and trading strategy to ensure that tailored organizational objectives are met and the maximum value of portfolios are realized.”
As the mortgage environment aggressively adjusts from scaling to meet customer needs to capturing margin in a severely contracting market, it will be important for all participants to get the most out of each asset.
BY DAREN BLOMQUIST
RYAN LILLY
I n the 10 years since the last housing downturn, mortgage in- dustry innovators have been laying the groundwork for success in both feast and famine. “We’ve set up a suite of services that is somewhat recession-proof, as long as we are capturing market share in those core functions,” said Ryan Lilly SVP of mortgage services with Phoenix, a Denver, Colora-
do-based company that provides a variety of services for mortgage servicers and companies trading mortgage servicing rights (MSR). The market appears poised to test this hypothesis as rising mortgage rates weaken demand, particularly for refinance home loans. Refinance originations decreased 21 percent year-over- year in the third quarter of 2018
to a new record low as far back as data is available — Q1 2000. The third quarter drop marked the sixth consecutive quarter with an annual decrease in refinance originations. Although not down as sharply, purchase originations in Q3 2018 decreased 2 percent from a year ago — also the sixth consecutive quarter with a year-over-year decrease.
Demand for mortgages is cooling even as interest in data- and ma- chine-driven innovation continues to heat up, and that combination is a potential recipe for excessive risk if not handled delicately, according to Kevin Marshall, president and co-founder of Clear Capital, a Reno, Nevada-based company that pro-
vides real estate valuations to the mortgage industry. “There is an appetite for analyt- ics. At the same time we have rising interest rates, and the potential softening of the economy,” he said, cautioning that analytics should be rigorously tested to ensure they stand up in a more volatile hous-
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FEATURED ARTICLE: DATA-FED DISRUPTION IN THE MORTGAGE MARKETPLACE
to look at the products available to them to make the right decision,” he said. “It doesn’t mean that these lenders are going to cut corners and say ‘woo-hoo’ let me go from a $500 appraisal to a $10 AVM.” Lenders shouldn’t think of AVMs as a wholesale replacement of apprais- als, but rather as just another option on a spectrum of property valuation tools that can be plugged into their decision-making process depend- ing on the type of property, type of loan and other factors, according to Cliff Lipscomb, vice-chairman and co-managing director at Greenfield Advisors, a Seattle-based firm that provides litigation and data analytics services to the mortgage industry. “AVMs have their place, just like appraisals completed by humans
have their place, and like appraisal reviews have their place,” said Lip- scomb, whose 42-year-old company recently introduced a new lend- er-grade AVM developed in part- nership with ATTOM Data Solutions. “Each of these tools has a role in mitigating the risk involved in a real estate transaction.” INNOVATION GRAVITY Since it was founded 17 years ago, Clear Capital has been operating in the tension between risk mitigation and optimized efficiency, according to Marshall, who noted that the company unsuccessfully tried to launch a prop- erty valuation Software as a Service (SaaS) soon after opening its doors. “We actually couldn’t sell it,” he
ing market. “We all have to be very mindful not to blindly accept analyt- ics that will negatively shine light on these progressive methods.” Marshall is an unabashed advocate for industry innovation — “What used to take weeks to do, we can now do in hours; it’s pretty cool,” he said — but argued that introducing untested innovation into the marketplace could backfire. “We are really big fans of keeping humans in the loop to make sure our methods are sound and be aware that any untested analytics could shine a very bad light and set back innovation in the industry for years,” he said. “We want the mortgage marketplace to be better and more efficient but we have to be really careful to pair analytics with humans as the market turns.” FLAG THE FRAUD Increasing fraud is also driving inno- vation in the mortgage space, accord- ing to Mark Richard, president with Foresight Information Services, a Co- lumbus, Ohio-based technology firm that provides data-driven products to the mortgage sector to help reduce the cost associated with application verification and fraud detection. “A recent study found one out of every 120 mortgage applications contained signs of fraud,” said Rich- ard, whose company was founded in 2011. “And this fraud rate is increas- ing. At the same time, the margins on loan applications are being squeezed. So, you have this situation where deeper and more thorough ex- amination and verification of applica- tions is necessary, but the economics dictate less time being spent.” Echoing both Lilly and Marshall, Richard believes a smart combina- tion of data-driven automation and human expertise will be needed to successfully combat rising fraud in a tight mortgage market. “I’m convinced the reliance upon
I’m convinced the reliance upon data-driven automated verification solutions will continue to expand so that manual examination can focus on the areas which are most suspect and prevent bad actors from walking away with a fraudulent loan. At the end of the day, we all pay for mortgage fraud through increased rates or even government-funded bailouts. Foresight’s mission in the mortgage space is simple: flag the fraud.
AVMs have their place, just like
appraisals completed by humans have their place, and like appraisal reviews have their place. Each of these tools has a role in mitigating the risk involved in a real estate transaction.
MARK RICHARD
CLIFF LIPSCOMB
data-driven automated verification solutions will continue to expand so that manual examination can focus on the areas which are most suspect and prevent bad actors from walking away with a fraudulent loan,” he said. “At the end of the day, we all pay for mortgage fraud through increased rates or even government-funded bailouts. Fore- sight’s mission in the mortgage space is simple: flag the fraud.” A sustained tension between risk mitigation and optimized efficiency is a hallmark of a healthy mortgage industry, according to Marshall with Clear Capital. He explained that a market too heavily weighted toward efficiency will be extremely bor- rower-friendly but could result in a housing bubble — exhibit A being the easy mortgage available in the run- up to the 2008 financial crash. On the other hand, a market too heavily weighted toward risk mitigation — which often comes in the form of heavy-handed regulation — can have a chilling effect on the market by introducing excessive friction in the loan origination process. “We always live in a tension of making sure we are pioneering for what the customer expects and THE RISK-EFFICIENCY TENSION
needs and wants, while also making sure we are not introducing systemic risk,” he said. “As long as we live in that tension we are pretty good.” The risk-efficiency tension is be- ing tested with a recent regulatory push away from full appraisals and toward automated valuation models (AVMs). A November 2018 proposal from the Office of the Comptroller of the Currency, the Federal Depos- it Insurance Corporation and the Federal Reserve calls for increasing the minimum home value for which a full appraisal is required as part of the mortgage origination process, from $250,000 to $400,000. Even if the proposal is adopted, it will be a bit of a non-issue for the industry in the short term given that Fannie Mae and Freddie Mac — which back the majority of U.S. mortgages — will still require ap- praisals in most instances, accord- ing to Marshall. “It’s not a mandate that you can’t get an appraisal, but it gives you op- tions for valuation, and maybe that’s an AVM,” he said. Even if appraisals are not required by regulatory agencies, lenders should carefully consider the prop- erty valuation options available and appropriate for a given situation, according to Marshall. “The lenders are going to continue
TOP 10 MORTGAGE ORIGINATORS: CHANGE IN MARKET SHARE
2018 MARKET SHARE
2017 MARKET SHARE
PCT CHANGE IN MARKET SHARE
6.00%
47%
5.00%
30%
4.00%
27%
3.00%
13%
10%
5%
3%
2.00%
-3%
-15%
1.00%
-22%
0.00%
Quicken
Wells Fargo
JP Morgan Chase
United Wholesale Mortgage
LoanDepot
Bank of America
Caliber Home Loans
Fairway Independent Mortgage
Guaranteed Rate
US Bank
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FEATURED ARTICLE: DATA-FED DISRUPTION IN THE MORTGAGE MARKETPLACE
“Evangelize these ideas early and allow people to vet them out before adopting them,” he said, noting that the Silicon Valley startup culture of quickly throwing untested innovation into the market place and failing fast does not work as well in the mortgage space where so much is at risk — particularly for the mammoth government-sponsored enterprises like Fannie Mae and Freddie Mac and big bank lenders. “You can’t just apply technology and analytics … you have to apply things with rigor and do a lot of back-testing ... (or) it can result in billions of dollars in losses for these big organizations.” Marshall said non-banks have been more open to leveraging data and technology in the mortgage orig- ination space.
market share and traditional banks losing market share compared to the first three quarters of 2017. Among the top 10 mortgage origi- nators in terms of origination counts in the first three quarters of 2018, the five with the biggest increase in market share were all non-banks: United Wholesale Mortgage, Fairway Independent Mortgage, Guaranteed traditional banks among the top 10 originators saw a decrease in mar- ket share compared to a year ago: Wells Fargo, Bank of America and US Bank. The exception to this was JPMorgan Chase, which posted a 5 percent increase in market share. While most of the top 10 origina- tors posted a year-over-year de- Rate, LoanDepot and Quicken. Meanwhile, three of the four
said, noting that the industry was not yet ready for such a tech-heavy solution, both in terms of psychology and availability of data. “The valua- tion data was stuck in a PDF form, so it was really hard to have high-level understanding of valuation condition and change over time.” While Clear Capital pulled back from the ahead-of-its-time SaaS product, the company continued to push the envelope when it came to leveraging technology for its valuation services, according to Marshall. In the wake of the Great Recession, the industry began to recognize the need for more data- and tech-driven solutions. “Once Freddie and Fannie intro- duced the uniform collateral data portal (in 2011) and other types of data, and started getting data in XML that’s when we started viewing the valuation industry as a data industry and not a PDF industry,” he said, adding that Clear Capital clients no- ticed the company’s internal analyt- ics were better than anything else in the marketplace and began to invest in those types of analytics for their own businesses. The push for innovation paired with patience for the industry to catch up is what Marshall refers to as “inno- vation gravity.” “We’ve always wanted to innovate just ahead of what the industry is will- ing to adopt,” he said. “Let’s do some really cool things today but let’s look ahead and think about what can be done because what can be done is a lot easier than what should be done.” The drive toward a digital mortgage is one example of where the concept of innovation gravity can be employed, according to Marshall. In the context of the digital mortgage, there is a gap between what can be done in terms of efficiency and transparency for borrowers, and what should be done in terms of introducing too much risk to the marketplace. That gap can be bridged by innovation gravity, Mar- shall said.
TOP 10 ORIGINATORS: PURCHASE MORTGAGE ORIGINATIONS
Q1 TO Q3 2018
Q1 TO Q3 2017
Quicken
Wells Fargo
JPMorgan Chase
United Wholesale Mortgage
LoanDepot
Bank of America
Caliber Home Loans
Fairway Independent Mortgage
We’ve always wanted to innovate just ahead of what the industry is willing to adopt. Let’s do some really cool things today but let’s look ahead and think about what can be done because what can be done is a lot easier than what should be done.
Garanteed Rate
US Bank
KEVIN MARSHALL
a 9 percent decrease in purchase originations. Again, the exception for traditional banks was JPMorgan Chase, which posted a 20 percent increase in purchase originations. STOP THROWING PEOPLE AT THE PROBLEM LendingHome is the epitome of a nonbank startup with tech roots that’s set out to disrupt the mortgage indus- try through data-driven innovation. “We saw the space as way too brick-and-mortar driven, way too paper-driven and just throwing peo- ple, people, people at the problem, and we thought we could do better,” said Matt Humphrey, co-founder and CEO of the Pittsburgh-based compa-
ny, which launched in 2013 and has since generated more than $3 billion in loans, primarily in the form of short-term bridge loans to fix-and- flip real estate investors. Although Humphrey initially had the broader mortgage marketplace with its average cost of more than $8,000 per mortgage origination in his sights, he decided to start with the low-hanging fruit of the fragmented fix-and-flip lending space, which his- torically has been the domain of local “hard-money” lenders charging dou- ble-digit rates on short-term loans. “These real estate operators are not being forced to go to the predatory local lender; they can have certainty of capital with us,” said Humphrey, noting that the typical hard money
loan charges 3 to 5 points up front and comes with a 12 to 15 percent interest rate while the typical LendingHome bridge loan is 1 to 2.5 points up front with an 8 to 10 percent interest rate.
“The non-banks are really inter- ested in grabbing market share, and they are all about the user experi- ence,” he said, noting that user expe- rience focus is good for the big banks as well because if they frustrate the borrower during the mortgage origination process it could put other business that consumer does with the bank at risk. “We and our lender clients are absolutely in the business of not frustrating the borrower.” An ATTOM Data Solutions analysis of publicly recorded mortgage origi- nation data in the first three quarters of 2018 shows non-banks gaining
crease in total mortgages originated, driven by a sharp drop in refinance originations, the majority of non- banks posted double-digit gains in purchase mortgage originations. United Wholesale Mortgage led the way with a 51 percent increase in purchase originations followed by LoanDepot (30 percent increase), Guaranteed Rate (25 percent in- crease), Fairway Independent Mortgage (19 percent increase) and Quicken (12 percent increase). Meanwhile Wells Fargo posted a 24 percent decrease in purchase origi- nations, and Bank of America posted
We saw the space as way too brick-and- mortar driven, way too paper-driven and just throwing people, people, people at the problem.
MATT HUMPHREY
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FEATURED ARTICLE: DATA-FED DISRUPTION IN THE MORTGAGE MARKETPLACE
“That's both because of the credit performance we've proven, and also the tech just stripped out so much cost of manually underwriting loans that we don't have to pass through to make those expenses back.” LendingHome’s origination plat- form eliminates traditional loan origination costs by leveraging data, including data on the property itself as well as on the prospective bor- rower and that borrower’s past per- formance with previous fix-and-flip projects. The data allows Lending- Home to “automate huge pieces of the underwriting process” while also constantly testing the accuracy of its upfront property value assumptions once the home flip project is com- plete, according to Humphrey. “We can oftentimes project very accurately what that after-repair value is going to be,” he said, adding that the data-driven efficiencies in the underwriting process can also help reduce approval timelines, which is especially critical in an industry oper- ating on extremely tight deadlines. “Borrowers in this space have to act fast; they're finding a property — it might be off-market — they have to find it, bring it to us and we have to be ready to give them an answer almost the same day, and ultimately close in let's say three, four, five, six days,” said Humphrey. “To give that level of service, to fully underwrite the loan with 20, 30, 40 different data points and the core credit attributes that we're looking at — that's hard to do without tech — certainly as you scale to the billions per year that we're now at.” LendingHome originated more than $844 million in loans in the first three quarters of 2018, up 35 percent from the first three quarters of 2017 and on pace for more than $1.125 billion in originations for the year, according to an ATTOM Data Solu- tions analysis of public record mort- gage data. Although LendingHome’s share of the overall mortgage orig- ination market stands at one-tenth
of a percent—in part because it's only focused on the niche fix-and-flip market segment—that market share has grown 48 percent compared to a year ago. DATA-FUELED DISRUPTION AND DISCOVERY Roc Capital is another recent en- trant to the fix-and-flip lending space that has experienced rapid growth since launching in 2014. “We add value by leveraging our deep Wall Street heritage, high-touch service, a custom end-to-end platform that makes lending fast, efficient and transparent,” said COO Maksim Stavin- sky, who noted that the company’s use of data-powered technology can be applied to many facets of the business. “We are using data and combining or- thogonal sources of data to help in the areas of risk, lead mitigation, fraud pre- vention, verification and sanity-check- ing of borrower-provided info.” Roc’s platform is driving disruption even in traditionally sacrosanct parts of the mortgage origination process.
“Our underwriters are now able to get preliminary title runs for submitted loans even before we get the report
from the title company,” he said, noting that these preliminary title checks are not used to close a loan but are useful as an initial check. Roc has also discovered additional opportunities within the space that can be supported by its data-driven approach, according to Stavinsky. “In addition to using data to support all aspects of our existing business, we also recently used data to get into a new business — insur- ance,” he said, referring to insurance for borrowers. “We worked with an A-rated insurance carrier to create an automated process for providing policies. Whereas our borrowers previously had to contend with a long application and days of waiting for a quote, today we are able to quote a policy in minutes, with minimal infor- mation required from the borrower.” The automated insurance approval process is fueled largely by the same property data Roc uses in other facets of its business, Stavinsky explained. “We have sufficient property-level data so as to obviate the need for the customer to provide any information,” he said. “Since most of our clients don’t love talking about insurance, this has led to great customer satisfaction. Insurance has never been this quick, easy and painless for customers.” tech-fueled startups such as Lend- ingHome and Roc begs the question: will the highly automated underwriting process these two companies and others employ open up a back door into the mortgage marketplace for the loose lending practices that ultimately led to the market’s downfall a decade ago? Both Humphrey and Stavinsky ar- gued that well-performing loans with low delinquency and default rates are critical for the continued growth of their businesses. That’s because both companies are selling the loans that LOAN PERFORMANCE LONG GAME The rapid growth of data- and
As we started to become an operating business and we started scaling, we were still always raising capital and so then we could actually point and say that data and very algorithmic approaches to underwriting this credit means that we can close loans in five days, not 20, but at the same time have two or three times as good loan performance.
We add value by leveraging our deep Wall Street heritage, high-touch service, a custom end-to- end platform that makes lending fast, efficient and transparent. We are using data and combining orthogonal sources of data to help in the areas of risk, lead mitigation, fraud prevention, verification and sanity-checking of borrower-provided info.
MATT HUMPHREY
was an intentional choice the company made to ensure the loans originated by its platform performed well, position- ing the company for long-term growth. “We wanted to play the long game, not the short game,” he said. “I think when you look at a space like fix-and- flip that a lot of investors had thought of as these are localized country club loans, these are kind of a weird dark corner of mortgage. We brought that transparency and that clean look to the space, and we've really brought broad, large-scale capital to bear.” BETTER THAN GUT INTUITION The quality of a loan’s performance depends heavily on the quality of its underwriting during origination, but that performance can also be impacted by how the loan is serviced, particularly in the event of delin- quency or a problem the borrower is facing that may lead to delinquency. The importance of smart, data-driv- en servicing is a lesson LendingHome and Roc have both learned in the laboratory of fix-and-flip lending. “Internally, data is useful in risk management to monitor delinquen- cy,” said Stavinsky of Roc, which services the loans it originates. LendingHome did not start out servicing its loans when it began orig- inating in 2014, but it soon discovered it could boost loan performance by ap-
they originate, and investors buying those loans won’t keep buying if the loans don’t perform as expected. “We transparently open up a really complete set of data to the end loan investor who buys that loan, whether that's a massive asset manager with hundreds of billions of assets or it's an individual peer-to-peer inves- tor with maybe 50 or 100K on our platform,” Humphrey said. “They get to the full historical platform perfor- mance of LendingHome’s now well over $3 billion in loans.” Loan performance also comes into play when startups like Roc and LendingHome raise venture capital, both Stavinsky and Humphrey noted. “As we started to become an oper- ating business and we started scaling, we were still always raising capital and so then we could actually point and say that data and very algorithmic approaches to underwriting this credit means that we can close loans in five days, not 20, but at the same time have two or three times as good loan performance,” Humphrey said. “That's where I think investors start to see the true value of the tech and data and un- derstand it's not just (we’re) doing well as a lender. That's a real sustainable, competitive advantage.” Humphrey noted that, before origi- nating any loans, LendingHome spent nearly a year building its lending plat- form from the ground up. He said that
MAKSIM STAVINSKY
LENDINGHOME LOAN GROWTH
ESTIMATED MORTGAGE ORIGINATION DOLLAR VOLUME
$844,477,410
$623,580,797
Q1 to Q3 2017
Q1 to Q3 2018
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FEATURED ARTICLE: DATA-FED DISRUPTION IN THE MORTGAGE MARKETPLACE
plying its technology to that aspect of the business, according to Humphrey. “I can tell you that within one year of taking servicing back in-house, run over our platform, just about every single metric, whether it was reso- lutions, timelines for disposition of assets, recovery rates and even costs, we excelled against anyone that we had assessed externally,” he said, not- ing that the company’s wealth of data allows them to work more intelligently with a borrower facing a problem. While the investor that owns the loan ultimately makes the decision on how to proceed in the event of a default, Humphrey said that investors have come to rely heavily on the rec- ommendations given by LendingHome “because our data platform performs a lot better than just gut intuition.” Companies like Phoenix are taking a more data-driven approach to servicing in the larger mortgage marketplace, according to Lilly, who noted that the servicing response to delinquency may be different de- pending on the investor. “For many banks, the objective has been mitigation of risk and speed in which assets can be liquidated from the portfolio,” he said, noting that much of the non-performing loan vol- ume lingering from the last housing crash has shifted from banks to pri- vate equity investors who purchased those loans at a discount. “Investors and private equity firms work to maximize the achieved value through a reduction in processing leakage and identifying the optimal balance between condition, timing and value.”
define loss reserves,” he said. “Under- standing what corporate advance rates are at various delinquency levels is key to developing a strategy for retained portfolios. It is also important to understand what advances will be re- coverable versus non-recoverable and what time looks like for recoverability. “For advances that are not recov- erable it is important to understand what events may have been control- lable or uncontrollable and who had the ability to impact those events — sub-servicers, vendors, etc.,” Lilly continued. “Many times, errors or incomplete tasks can lead to indem- nification for events that resulted in curtailment and eventual loss.” SERVICING SCAR TISSUE Marshall with Clear Capital noted that servicers learned the hard way how not to handle a surge in defaults during the last housing downturn. “If you look at the speed at which servicers had to ramp up in 2009, 2010, as a result we saw a lot of blow- back on those processes,” he said. “Whether it was robo-signing scan- dals or unfairly evicting borrowers — all the junk that we dealt with.” The wounds from that experi- ence have forced servicers to adopt platforms and processes that should perform better in a high-default en- vironment, according to Marshall. “The scar tissue from those years will really pay dividends the next time around,” he said. “(It) forced us all to act with more rigor as we manage the
Our goal is to ready a new approach and technology-enabled platform to play offense to the next cycle.
RYAN LILLY
noting that Phoenix has been investing in data-driven tools for dealing with non-performing loans even though de- linquencies have been down in recent years. “Unlike most participants in this space, Phoenix has allocated capital earned during the crisis to reinvest it in REO through the application of auto- mation, machine learning and business intelligence. In the same way, we have been applying this logic to servicing oversight. Our goal is to ready a new approach and technology-enabled plat- form to play offense in the next cycle.” The servicing of loans backed by Ginnie Mae is a focus for Phoenix, said Lilly. That’s because owners of MSR portfolios with Ginnie Mae- backed loans are required to shoul- der the costs of processing defaults in advance of foreclosure, with those advances not recoverable until post-foreclosure — if at all. “Understanding the true cost of Gin- nie servicing will help organizations more clearly strategize efforts to attain the targeted ROI and more accurately
next default boom. If we go through this next cycle, my goal is that the industry can do it with more empathy so that borrowers are not as soured on home- buying as they were in 2008, 2009.” JUST GETTING STARTED Marshall and other experts inter- viewed are optimistic that, if imple- mented properly, data-fed innova- tion can ultimately improve both the user experience and reduce risk in the mortgage marketplace. “We are trying to very thoughtfully apply machine learning, AI. We are trying to artfully use some of these analytic tools to understand collateral change,” Marshall said. “Rather than our innovation used just to generate investment, (we are) keeping humans in the loop and iterating forward in a measured approach so we are intro- ducing true progress and not just in- troducing risk into our client’s shops. That’s something we’ve earned the right to do because we have shown that we care about client risk.” Stavinsky of Roc and Humphrey of LendingHome both believe the success their companies are experi-
We're just getting started; we feel there are endless opportunities to improve on current industry gold standard systems and processes. We can envision disruption in nearly every facet of the business including appraisal, closing, draw disbursement, insurance, just to name a few.
MAKSIM STAVINSKY
encing in the fix-and-flip lending lab- oratory can eventually be replicated in the larger mortgage marketplace. “I would say that we've built a gen- eral purpose residential mortgage platform,” said Humphrey. “While we have our technology and risk model today pointed towards the space of fix-and-flip, we're constantly look- ing at data and (considering) new products and new opportunities. So those new products, new opportuni- ties could be really close adjacencies to bridge — more on the construction side, rental side, things like that. Or they could, someday in the future, be 30-year consumer mortgages.”
“We’re just getting started; we feel there are endless opportunities to improve on current industry gold standard systems and processes,” Stavinsky said. “We can envision disruption in nearly every facet of the business including appraisal, closing, draw disbursement, insur- ance, just to name a few.”
PLAYING OFFENSE IN THE NEXT CYCLE
We are trying to very thoughtfully apply machine learning, AI … we are trying to artfully use some of these analytic tools to understand collateral change.
Investing in data and technology to drive decision-making for servicers is key, according to Lilly. “Assembling a complete dataset in combination with third-party tools can help clearly identify the right path to meet these objectives,” he said,
Daren Blomquist is vice president of market economics at Auction. com, the nation’s leading online
marketplace for residential bank-owned and foreclosure properties. Learn more at www.auction.com.
KEVIN MARSHALL
12 think realty housing news report
february 2019 13
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TECH-FUELED CASH BUYERS: HOME PURCHASES
OPENDOOR
OFFERPAD KNOCK
ZILLOW
16,000
14,000
12,000
10,000
8,000
6,000
4,000
MY TAKE
iBuyer Growth Grounded in Speed, Simplicity and Certainty of a Cash Purchase
2,000
0
2014
2015
2016
2017
Jan-Oct 2018
Cortney Read, director of commu- nications and outreach at Offerpad. “We actually have customers that sell to us and buy Offerpad homes and they are able to do those trans- actions within a month.” THE EVOLUTION OF IBUYERS In the beginning were tradition- al real estate investors, the early ancestors of iBuyers who have long leveraged the advantage that speed, simplicity and certainty give them when purchasing a home with cash. But it’s clear that while iBuyers may share some of the same DNA as traditional real estate investors, they are a completely different species. From the outset iBuyers were poised to be different from tradi- tional real estate players because of their roots in Silicon Valley. Those roots provide them access to the deep pockets of venture capital
looking for a disruptive real estate model as well as access to the big data and technology talent that could deliver on that disruption. First to market in 2014 was Open- door, the epitome of Silicon Valley roots combined with an affinity for real estate investing. Prior to found- ing the company, CEO and Co-Found- er Eric Wu founded geo-data analytics company Movity, which was acquired by Trulia. Wu also co-founded Rent- Advisor.com, and his side hustle is a real estate fund that has invested in more than 100 multi-family units. Others on the Opendoor leadership team come from brands that are virtually synonymous with Silicon Valley: Uber, Square, Groupon, Yelp and PayPal. That pedigree helped the company raise $1 billion in venture capital funding since 2015. Not far behind Opendoor was Offerpad, which began buying homes directly from homeowners via cash offers in 2015. Offerpad’s lineage
is more heavily steeped in the real estate world: one of its co-found- ers was a Realtor prior to founding the company; its other co-founder previously founded Invitation Homes, a company that purchased tens of thousands of homes in the wake of the Great Recession, often buying with cash at the foreclosure auction. Still, Offerpad’s cachet with the ven- ture capital crowd has helped it raise $410 million in funding since 2017. The influx of venture capital has allowed these first-to-market iBuy- ers to ramp up quickly in terms of number of transactions. An ATTOM analysis of public record data shows Opendoor purchased just 14 homes in 2014, then 471 in 2015, 1,529 in 2016, 3,626 in 2017 and 9,578 in 2018. Offerpad started with 13 purchases in 2015, jumped to 559 in 2016, then 2,022 in 2017 and pur- chased 3,110 in 2018. Knock was another early entrant le- veraging the speed/simplicity/certain-
BY ROB BARBER
C ash is king in a home sale — and cash buyers are often able to buy below market value — be- cause cash represents speed, sim- plicity and certainty for the home seller. More to the point, sellers at- tach some monetary value to speed, simplicity and certainty in a home sales transaction (see sidebar on p. 27 for more details on this). The opportunity to add value to the home sales process with a quick, clean and certain cash sale is the foundation for the nascent iBuyer business model. “The number one thing is you’re putting the control back in the seller’s hand. Before Offerpad there wasn’t much control they had or certainty over the process,” said
THE CASH PURCHASE DISCOUNT
MEDIAN SALE PRICE MEDIAN ESTIMATED VALUE AT TIME OF SALE
PREMIUM/DISCOUNT
1.3%
$259,375
$256,000
$178,000
$203,000
-12.3%
2018 Financed Home Purchases
2018 Cash Home Purchases
16 think realty housing news report
february 2019 17
MY TAKE: iBUYER GROWTH GROUNDED IN SPEED, SIMPLICITY AND CERTAINTY OF A CASH PURCHASE
TECH-FUELED CASH BUYERS: HOME SALES
Median Purchase Price
Median Sale Price
Gross Margin % Purchased in Foreclosure or Bank-Owned
Median Year Built
Median Square Footage
Avg Days Held
OPENDOOR
OFFERPAD KNOCK
ZILLOW
All Flips
$150,000
$213,000 $63,750 $244,500 $15,500 $224,900 $21,550
30.4%
1975 2002 1999
1,368 1,821 1,678
178
Opendoor $229,000 Offerpad $203,350
6.9% 8.5%
80 88
12,000
10,000
sold close to 1,800 — the iBuyers aren’t banking on the deep discounts that come with the combination of a cash purchase and a distressed property. When done at large enough scale and velocity, the added value that comes with the speed, simplicity and certainty of a cash sale creates sufficient margin on its own — with- out the distressed element added in. At least that is the theory. ATTOM data on homes flipped — sold for the second time in the last 12 months — in the third quarter of 2018 demonstrates how the iBuyer business model is fundamentally different from the traditional home flipping business. ATTOM compared the most prolific seller entities associated with Open- door and Offerpad to the overall home flipping market in the third quarter and found that the iBuyer entities are transacting on newer and larger homes that are much less likely to be distressed than the overall market. Additionally, the two iBuyers operated on substantially thinner gross mar- gins — sale price minus the original purchase price — than traditional flippers but resold homes more than twice as fast as traditional flippers.
THE CONVENTIONAL WISDOM THAT CASH IS KING IS WELL-SUPPORTED IN PROPERTY DATA
8,000
A look at proprietary home sales data from the nationwide ATTOM Data Warehouse demonstrates the power of a cash purchase. The data shows more than 2.2 million single family homes and condos were sold to buyers using financing through the third quarter of this year. The median sales price on these financed purchases was $259,375 — 101 percent of the median estimated market value of those same properties at the time of sale. There were more than 828,000 homes sold to cash buyers through the first three quarters of 2018 with a median sale price of $178,000 — 88 percent of the median estimated market value of those same homes at the time of sale. The estimated market value is based on an automated valuation model (AVM) from ATTOM. A more nuanced analysis of ATTOM public record sales data by BYU economics professor Jaren Pope in 2017 yielded similar results. Controlling for location of home, housing characteristics, time of sale and a host of other characteristics that may impact home price, Pope’s preliminary analysis found that homes sold to cash buyers sold for 5 to 10 percent less than comparable homes. The cash discount is part of the calculus figured into the Knock business model, according to co-founder and CEO Sean Black. “With Knock’s Home Trade-in program, we buy our customers’ new home on their behalf, making their offer more competitive and getting them a 3 to 5 percent discount,” he said. “This is before helping them sell their old house on the open market for the best possible price. This ensures they get the most value out of their equity on both sides of the transaction, and enables Knock to deliver them with a convenient, certain experience throughout the process.”
6,000
4,000
2,000
0
2014
2015
2016
2017
Jan-Oct 2018
ty value-add of an all-cash purchase. The ATTOM analysis shows entities associated with Knock purchased 357 properties between 2016 and 2018. Knock has a different spin on the model, purchasing a new home — with cash — for a prospective home seller before moving that home seller out of his or her current home and then selling that current home. “We don’t consider Knock to be an iBuyer, as their ‘instant offer’ to buy your old house only addresses one side of the transaction, which is simply not enough to transform real estate,” said Sean Black, co-founder and CEO. “We believe certainty, convenience and cost-effectiveness are needed to provide home buyers and sellers with a better experience. iBuyers do not solve for cost because they are flipping
homes for profit; 71 percent of home sellers are buying their next home at the same time, and iBuyers leave them with no solution for buying and take a chunk out of their equity.” Keep in mind, the aforementioned numbers are just purchases. In theory, these entities are subse- quently reselling every property that they purchase, typically within just a few months. The ATTOM analysis shows that Opendoor, Offerpad and Knock combined sold 16,574 homes between 2014 and 2018. The rapid growth of these early entrants caught the attention of more mainstream players like Zillow and Redfin — who at one point not too many years ago were themselves at the bleeding edge of technology and real estate. Both companies have
jumped into the iBuyer space, al- though they still have much ground to gain on the early entrants. ATTOM data shows entities associated with Zillow purchased just two homes in 2017, and 549 in 2018, while entities associat- ed with Redfin have purchased 145 properties in three Southern California markets in the last two years. As the nascent iBuyer industry quickly matures, even more estab- lished real estate players are joining the fray. The legacy real estate broker- ages of Keller Williams and Coldwell Banker both made announcements about their involvement in iBuying programs in September 2018. Keller Williams said it has been testing the iBuyer concept in an undisclosed mar- ket for more than a year, while Cold- well Banker announced the launch of
its own iBuyer program in Atlanta and Dallas, expanding to Tampa.
nance and other distressed markets in an effort to deepen the purchase discount and pad the eventual profits when the home was resold. That traditional home flipper model works when operating with lower volumes — the ATTOM Data Solutions Q3 2018 Home Flipping Report shows home flippers aver- aged 1.21 completed flips during the quarter. But at a much larger scale — Opendoor purchased more than 2,700 homes in the third quarter and
Rob Barber is CEO of ATTOM Data Solutions, curator of
THE IBUYER DIFFERENCE The emerging iBuyer businesses differ from traditional cash buyers not only in the volume of purchases — enabled by the influx of institution- al capital — but also in the types of properties they are buying. The tradi- tional cash buyer targeted distressed properties with deferred mainte-
the nation’s premier property database. A 25-year veteran in the real estate information services industry, Rob directs the ongoing product innovation that leverages the company’s data warehouse and data delivery platforms
which fuel real estate transparency. Learn more at ATTOMdata.com.
18 think realty housing news report
february 2019 19
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20 think realty housing news report
TOP 10 STATE PROPERTY TAX RATES
People fly in from other states to Dallas, Austin and Houston for the day and then fly home. They show up and bid on a couple hundred properties in Texas.
AVERAGE OF TAX AMOUNT
EFFECTIVE TAX RATE
AARON AMUCHASTEGUI
Pennsylvania Connecticut
New York
New Hampshire
Ohio Wisconsin
New Jersey
Illinois Vermont Texas
JAN-NOV 2018 SCHEDULED FORECLOSURE AUCTIONS
MARKET SPOTLIGHT
Taste of Texas
from Colorado, New Mexico, California, Louisiana, Arkansas and Oklahoma. Texas also had the highest percentage (93.4 percent) of residents applying for a purchase mortgage who wanted to remain within the state’s borders. Statewide unemployment, which most recently topped out at 8.3 per- cent between August 2009 and March 2010, has dramatically dwindled to 3.7 percent as of November 2018. Between population growth and job growth alone, it is easy to understand why Texas has been, and continues to be, a popular place for investors looking for passive income from long- term cash flow and appreciation. “The only downside with investing in Texas is the property taxes are really high,” said Amuchastegui. “But it is a landlord-friendly state. You can evict someone in just two to three weeks.” With the help of data and local mar- ket experts, I've assessed real estate investing opportunities in the state’s five largest metro areas — Austin, Dal- las, El Paso, Houston and San Antonio.
Texas
New Jersey
BY JOEL CONE
E verything’s big in Texas, including the foreclosure auctions. A total of 27,324 Texas properties were scheduled for public foreclo- sure auction in the first 11 months of 2018, the most of any state and accounting for one in 10 scheduled foreclosure auctions nationwide, according to ATTOM Data Solutions. Texas foreclosure auctions are on track to increase 12 percent in 2018 compared to 2017, the first annual increase since 2014 but still well below the peak of more than 126,000 sched- uled foreclosure auctions in 2006. In Texas, foreclosure auctions are on the courthouse steps on the first Tuesday of each month. “There’s not as many foreclosures as we used to have. People fly in from other states to Dallas, Austin and Hous-
Florida
ton for the day and then fly home. They show up and bid on a couple hundred properties in Texas,” said Aaron Amu- chastegui, co-founder of HomeRock, LLC, who, with his support team, prepares a list of potential properties in those three metro areas to bid on every month. “The trick is having a big list when you come in. Most investors target three or four counties a month.” With an estimated population gain of 1.34 percent in 2018, not only is Texas the home to 8.75 percent of the nation’s population, it’s also a very popular state for people to relocate, according to a state migration study published by LendingTree. Based on the study of 2 million purchase mortgage requests, Texas is a top destination choice for people thinking about moving out of state
California
Illinois
Pennsylvania
New York
Ohio
Georgia
Virginia
Maryland
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