How artificial intelligence could change the -2-

When it comes to adopting new technology such as AI, "real estate has always been a bit of a laggard," Alex Wolkomir, a partner at consulting firm McKinsey & Co., told MarketWatch.

Until now, the industry has seen little need for it. After all, home sales rocketed in recent years due to record-low mortgage rates, and the booming status quo didn't incentivize interest in trying new technologies. On top of that, "a lot of technology that is relevant to real estate was not mature," Wolkomir said, "because so much of real estate is still physical."

Staircase, a New York City-based startup, recently launched its flagship product called ChatMTG. The text-based chat platform offers a 10-minute mortgage-application process that uses simple data and is vetted with AI. Plug in all of the necessary information - from pay stubs to bank statements - and the bot will put together an application.

The goal is to use the bots to eliminate the middlemen involved in the mortgage process, Soofi Safavi, co-founder and chief technology officer at Staircase, told MarketWatch. Those intermediaries "collect a significant amount of compensation for it, [when one can do] that with bots," he said.

Plus, the technology helps Staircase offer a mortgage rate that's 1.25% lower than the standard, Safavi noted - which can total hundreds of thousands of dollars in savings over a 30-year mortgage.

The drawbacks

At a time when the industry is facing headwinds due to mounting problems in the commercial real-estate sector, slower rent growth, rising home prices and high interest rates, offering to save folks some money seems like an attractive proposition.

But as with every promising and emerging technology, there comes unintended consequences.

One of those consequences is the amplification of discrimination. Since algorithms get their data from current sources, there is a possibility that they consume significant amounts of flawed or questionable data points, and spew out a less-than-ideal outcome.

In 2016, ProPublica published a deeply reported story about how AI used to predict the likelihood of a person committing a future crime contained racial biases.

In the real-estate sector, algos can also perpetuate discrimination against people of color, as they ingests property data going back decades - including periods when Black people were actively discriminated against and denied property.

"People of color are not represented in the data ... [and so] structural, systemic issues that are well known in housing will be perpetuated by AI systems," Michael Akinwumi, chief responsible AI officer at the National Fair Housing Alliance, told MarketWatch.

Federal regulators are aware of this so-called digital redlining. The Consumer Financial Protection Bureau said it's prioritizing this issue, to make sure that people are protected from algorithmic bias.

That's in addition to automation bias, Akinwumi noted. "Based on your skin tone, some of the algorithms that are behind the facial-recognition technology are over-criminalizing residents of color in certain areas," he said. In 2023, the Washington Post published an investigation that revealed how surveillance cameras were being used to punish and evict residents of public-housing projects.

"As humans, we often overrely on technology and assume anything that is coming out of the system is perfect, is objective. But there's a lack of oversight," Akinwumi added.

And so as AI becomes part of people's daily lives, it also has the potential to "turbocharge fraud and automate discrimination," Lina Khan, the chair of the Federal Trade Commission, observed last April.

'It's become sort of a daisy chain'

But for now, the real-estate industry is still trying to figure out how to actually use the new technology.

Back in Dayton, Katie Hill is trying to figure it out. On her platform Unlisted, Hill brings homeowners and home buyers together - all completely off the grid, or multiple listing services. No home sold appears on public-facing websites like Zillow.

Instead, when a home buyer searches for a property, the company curates, scores and ranks a list of homes specific to what they're looking for, from its database of 121 million homes.

Once Unlisted figures out which homes fit the buyer's preferences, its software figures out how likely it is that those homes will sell - a similar model to Realeflow's.

"The higher the score for that search, the higher the home is ranked and presented to the buyer as a promising opportunity for that specific buyer," Hill explained.

Hill's company also invites homeowners who are identified as having desirable homes that other people would want to buy to sign up for the platform. They don't have to sell immediately; rather, the platform asks when they might be ready to sell. This information is relayed back to the buyer, and feeds into an algorithm that informs how likely other similar homes will sell. "As the responses increase, the algorithms are further informed and refined, and the predictions become more accurate," Hill said.

For homeowners, the goal is for the platform to "signal, subtly, that they're opening [up] to selling," which will eventually help the company match them with eager buyers, Hill said. "It's become sort of a daisy chain where you can start to put together" people who are looking to sell in a couple of years with people who want to buy during that specific time frame, she noted.

So far, Hill says Unlisted has reached out to some 1,000 homeowners in 14 cities - and since October has facilitated the sale of six homes, all off the market.

-Aarthi Swaminathan

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05-25-24 1119ET

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