Robot Landlords Are Buying Up Houses
Companies with deep resources are outsourcing management to apps and algorithms, putting home ownership further out of reach.
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Founded in 2016, Imagine Homes is linked to Colchis Capital Management, a deep-pocketed West Coast investment fund interested in companies that automate and simplify real estate transactions. Unlike most of the larger mass renters of single-family homes, they haven’t opened leasing offices in any of the cities where they operate—Pittsburgh, Cleveland, Cincinnati, Minneapolis and St. Louis, according to The Automated Landlord, an expansive look at the role of technology in the Wall Street grab of houses, published in the February 2022 issue of the journal Environment and Planning.
The company, which did not respond to multiple requests for comment for this story, has not specified its number of employees. By most indications, it is a scrappy outfit, with 35 employees listed on LinkedIn and 50 to 200 estimated by Indeed, all to manage 1,500 houses across four states and to rapidly acquire more. It outsources and automates most of the tasks that traditional landlords do.
At a time when escalating home prices are pushing more people out of the prospect of ownership, landlord automation doesn’t just help wealthy investment firms own an increasing percentage of the U.S.’s small homes—it makes the whole paradigm possible.
Think of a landlord. Not just a landlord, but a representation of that class of people. Depending on your experiences (and level of class rage), maybe you picture a jolly old guy who occasionally comes by with a wrench to fasten up a pipe or maybe you seen the dumpy modern incarnation of a feudal lord, siphoning off your income through accrued wealth and land deeds. Maybe it is a corporate representative of a large apartment complex.
Regardless, to function as a landlord, one traditionally needed to do some legwork—or at least have someone do it—enough to show places to applicants and oversee maintenance. For a landlord looking to expand, they also required deep knowledge of a local housing market and willingness to spend countless hours looking for and developing new properties.
This once limited the market of single-family home rentals to small-time landlords or companies that, at most, had properties across one metro area. But this sector was of little interest to Wall Street.
“The single-family rental market was very opaque, because the ownership was so fragmented,” Desiree Fields, an associate professor of geography and global metropolitan studies at the University of California, Berkeley, who wrote the Automated Landlord paper, told Motherboard. “Because of that, it was impossible to do things like securitization or real estate investment trusts”—the complex financial instruments that Wall Street uses to extract money from investments.
Fields completed dozens of interviews with tech vendors and employees at Wall Street rental companies for the Automated Landlord paper.
After the 2008 crash, data brokers like CoreLogic and RealtyTrac began producing heat maps of foreclosures. “Those kinds of advances really enable institutional and large scale financial actors to know a market at a distance without having that kind of intimate, tacit knowledge that comes from actually knowing a place,” said Fields.
Soon, new securities-backed companies were buying vast quantities of small homes (many of them foreclosures) with plans to rent them out. Some of these companies have ballooned into behemoths. Invitation Homes, the largest, has more than 80,000 houses in 16 metro areas. American Homes 4 Rent, founded by self-storage magnate B. Wayne Hughes, has more than 58,000 in 22 states. Even Amazon boss Jeff Bezos has bought into the remote management trend with Arrived Homes, a platform that buys up houses and offers shares to real-estate speculators hoping to turn a profit.
Institutional investment companies own only 3 percent of the single-family home rental market, but they have saturated some areas, like Atlanta, where they own about one in five single-family rentals and are amassing more.
Housing advocates and progressive lawmakers say these types of companies further push lower and middle-income Americans out of homeownership by buying up the kind of older, 1,000-square-foot-ish houses once affordable to first-time homeowners and inflating the market with investors.
There isn’t much data of automated landlords' effect on home prices yet, Brendan McKay, president of advocacy at the Association of Independent Mortgage Experts, told Motherboard. “But it's pretty easy to draw a straight line to the fact that it is making it significantly harder for low- to moderate-income families to become homeowners, because that’s the market that they're buying. So it is absolutely disenfranchising that segment of people.”
Automated landlord companies also use data tools to find and buy up houses at a brisk pace. In her paper, Fields describes “acquisition engines” used to rapidly build these vast portfolios. Housing data is fed into an algorithm, which savors it for neighborhood desirability and amenities, proximity to employment centers, transportation corridors, construction type, and repair needs. Wall Street-backed landlords then use this data to make split-second decisions on which houses to buy. It’s reliable enough, to them, to forego the visual inspection almost any small-time landlord would consider a must.
Imagine Homes—which stretches the robot landlord concept by not even having offices in places where it leases—has recently been on a buying spree. According to search results from local real estate directories, in the last year, an LLC connected to the company purchased 27 houses in Cuyahoga County (home of Cleveland), 49 in Hamilton County (home of Cincinnati) and five in Franklin County, presumably to get a foothold in the Columbus area. Rarely does the company purchase a house for more than $200,000.
It sometimes puts in bids hours after houses go on the market, bids that few others could beat, incentivizing the seller to sell quickly.
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