Could Buying and Selling a House Be As Easy As Stock Trading?

September 17, 2019
Photo by Markus Spiske on Unsplash

MarketWatch reports on the latest bid by algorithms to grab a piece of the $74 billion paid in real estate agent commissions last year.

Columnist Andrea Riquier writes about the iBuying business models of Zillow, Knock, and HouseCanary. The three companies use their digital platforms to estimate the value of a home and make an all-cash offer to buy a house. If the owner accepts, the company buys, owns, and resells the home and charges a fee for the service. The process is an alternative to the stress of traditional real estate transactions that can take months of showings.

Zillow, whose core business is selling leads to real estate agents, dove into iBuying last year with Zillow Offers. Unlike other companies that have data about listings, Zillow claims its secret sauce derives from the demand side, in particular the 180 unique website visitors each month and the machine learning that will ensue from analyzing where and what they’re looking for.

Knock bills itself as a real estate concierge service and developed an automated home valuation model called Borg. The platform goes beyond comparables with neighborhood listings and includes data about upgrades, home style, room sizes and more. HouseCanary aggregates “millions of data elements” to calculate home-price valuations in real time.

The question remains: How much of what comes next comes down to algorithms, and how much to process? For now, the onslaught of machine learning in the housing market continues unabated.

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