AI tech takes aim at resi industry investors

Big data providers race to develop products to better match institutional investors with single-family home listings

Entera founder Martin Kay and single family homes (Credit: Entera and iStock)
Entera founder Martin Kay and single family homes (Credit: Entera and iStock)

The next big arms race in institutional residential investing may just involve artificial intelligence.

A handful of companies are developing ­big data technologies to help institutional investors find the homes they want and buy them in bulk, according to the Wall Street Journal.

That’s allowed their customers, like hedge funds and private equity investors, to scoop up more homes faster than ever before.

Firms including Entera Technology, Progress Residential and Amherst Residential each feed thousands of data points into their algorithms to find suitable investments for their institutional clients. That includes listing information like age of the property, the number of rooms and square footage.

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Institutional investment in single-family real estate in particular spiked in the wake of the economic crash, which has made the market more competitive. Algorithms could help investors find yield where they may not have looked before.

Entera processes more sophisticated data like a home’s orientation and location of its kitchen, and the amount of light it receives during the day. The company’s computers can also scan listing photos to find images of a sunny kitchen based on similar photos they have fed into the machines.

It also scans data to see if a yoga studio or Starbucks — which could indicate a gentrifying neighborhood — has opened nearby recently.

Amherst’s technology can also project the cost of potential renovation work — based on jobs on similar properties — giving the investor a look ahead, according to the Journal. [WSJ] — Dennis Lynch 

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