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The Five Key Ways Residential Real Estate Investing Will Change by 2020

Residential real estate is the largest asset class in the world, amounting to a whopping $36 trillion* in the United States alone.

How residential properties investment will change by 2020

Despite the real estate market’s size and importance, however, there has been little innovation around related applications, analytics and technology. As a result, homeowners, investors, realtors and lenders have had to limp along using outdated methods when tackling properties valuation – and this led to fragmented, incomplete and inaccurate data for decision making.

Or at least that’s the way it has been until recently.

New real estate-specific tools are finally beginning to emerge, and they’re poised to revolutionize how property values are determined, how loans are underwritten, and how market trends are forecast.

What do you need to know to keep ahead of the residential real estate curve?

Here’s my short list of the five key changes on the horizon:

  • Residential real estate values will become more accurate and trusted. It’s now possible to create enormous data sets that combine MLS and county assessor records, macroeconomic data, capital markets data, mortgage records, house/parcel data, search and social data, etc. These data sets can then be leveraged using sophisticated analytics to significantly improve the way real estate values are calculated and forecast. In fact, recent testing completed over the second quarter of 2016 found that HouseCanary valuations had a national median error rate far better than our next closest competitor. Even greater accuracy gains are expected, and that means that within the next few years, homeowners, investors, realtors, appraisers, and lenders will be able to turn to a single trusted resource when making real estate decisions –a resource analogous to the Kelley Blue Book consumers use when buying cars.
  • Homeowners and residential real estate investors will benefit from personalized, data-driven apps. You’re probably familiar with Google Calendar, the popular time-management app that can remind you when it’s time to leave home for your next appointment, provide an optimal route to your destination, tell you how long it’s going to take to get there and inform you of traffic tie-ups.  Imagine how decision-making would change if homeowners and investors could leverage that level of personalization, clear direction and ability to execute regarding the residential properties they own (or want to own). Need an alert when mortgage rates have met a certain threshold? Curious about how home value trends and interest rates impact your eligibility for a home equity loan? Wondering about the current value of your property—and how that value might change in the next few years? When apps provide real-time information relevant to your real estate needs, you’ll be empowered to make better, more timely decisions.
  • Machine learning will optimize residential properties search. Technological advances will enable consumers, realtors, investors and lenders to mine massive real estate data sets in order to find opportunities that best fit their needs. For instance, after calculating what constitutes an affordable mortgage, a prospective homeowner will be able to search for residential properties that meet that criteria based on geography, market risk and/or other trends. Likewise, investors could easily identify properties that offer a certain rate of return or other defined characteristic.
  • Real estate transactions will become faster and easier. These days, the average real estate transaction takes more than 100 days, or 3 ½ months, to complete—generally, it takes about 60 days for a seller to find a buyer, and then after that, another 45 days for the buyer to secure financing. Once it’s easier to obtain accurate and trusted data (see #1 above), these waiting periods will shrink dramatically. Down the road, I wouldn’t be surprised to even see “instant” offers and loan underwriting for many, if not most, residential properties in the U.S.
  • Open technology architecture will allow customization for real-time decisions and improved asset management. HouseCanary products are based on open technology architecture with APIs that will allow developers, mortgage companies and others to access information and analytics in minutes. Now that there is data available on every property nationwide, the opportunities are endless, and we can all look forward to new and unique applications that yield improved understanding and faster, better decisions regarding the real estate market.

At HouseCanary, we are focused on building around these five trends, which we believe will have a huge impact on the largest asset class in the US and the world. Over the past several years, the real estate sector has seen its fair share of new rules and regulations, but the way real estate decisions are made has remained largely unchanged. As these trends take shape, they’ll fuel innovation that we can’t even foresee. I anticipate the promise of technology, big data and predictive analytics will finally take hold, transforming how consumers, investors, realtors and lenders alike make real estate decisions.

* The $27T home value market is calculated as $14T in homeowner equity + $13T in residentials mortgages. If we add the $9T in residential mortgage backed securities (the packages of mortgages put together and resold to financial investors), the residential real estate industry tops out at $36T.

Jeremy is the co-founder and CEO at HouseCanary. He drives the company's vision, strategy and growth to identify interesting and unique ways for leading corporations, investors and individual homeowners to use data to maximize their value in real estate. Jeremy was previously a Partner & Managing Director at The Boston Consulting Group where he helped leading real estate investors deploy billions in capital. In looking for ways to better predict real estate prices Jeremy began collaborating with Chris and Key in 2013. Jeremy received his MBA from The Wharton School, and his BS in Accounting from the University of Southern California with highest honors.

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