- Real estate companies are increasingly using artificial intelligence in every aspect of buying, selling and home financing.
- Algorithms can now go through millions of documents in seconds, looking through property values, debt levels, home renovations, and even some of a homeowner’s personal information.
- “The traditional agent would go knock on the doors of a lot of homes. Now AI helps you find the homes that are most likely to sell in the next 12 months,” said Compass’ chief technology officer.
Brick-and-mortar real estate may seem like the only tangible thing left in an increasingly virtual world, but it too is being taken over by artificial intelligence.
Some of the biggest names in the business, such as Compass, Zillow and LoanSnap, are now employing AI to help find buyers the perfect mortgage and the perfect home. And for real estate agents, it may already be a game-changer.
Most real estate data is public, from land records to title documents, purchase price and even mortgage liens. The trouble was it was an onerous process to go to local offices and obtain all the information. Not anymore. Computer algorithms can now go through millions of documents in seconds, looking through property values, debt levels, home renovations, and even some of a homeowner’s personal information.
At LoanSnap, a San Francisco-based mortgage lender, AI is used in various steps of the mortgage process, from finding the perfect loan type for a borrower to finding the right investor for the loan.
First the borrower’s financial information is put in. Then the system “takes all that information, forecasts it out into the future and looks at thousands and thousands and thousands of options,” said Karl Jacob, CEO of LoanSnap. “That’s different ways of paying off debt, different loan options, and this is one of the first times AI has been turned into something that helps consumers versus harms consumers.”
And for refinances, he said, “We’re building a financial model for someone, and showing them exactly how much money they’re losing on a monthly and yearly basis, and then showing them how they could potentially fix that issue and save money in the future. Again, in seconds.”
Jacob admits that pretty much every company now claims to use AI in some respect but said not all are really applying it to its full potential.
“Ninety-five percent of it is rhetoric, right? It’s a popular term. People glom on to things like that and say, ‘Oh yeah, we use AI too.’ AI is actually machines thinking and/or looking at possibilities that would not have been looked at before,” he added.
So AI can be helpful for borrowers, but it also seems like the holy grail for real estate agents hunting for listings in today’s ultra-competitive housing market. The supply of homes for sale has hit several record lows since the start of the pandemic, when buyer demand suddenly took off. Agents are desperate to find new listings, and AI is providing a new entrance.
“The traditional agent would go knock on the doors of a lot of homes. Now AI helps you find the homes that are most likely to sell in the next 12 months, and it does so by triangulating all the data associated with the home, like when the home last sold, how long the owner has occupied the home, what rate the home sells at in that particular area,” said Joseph Sirosh, chief technology officer at Compass, a real estate brokerage.
AI “triangulates all of that information to predict which home is likely to come for sale, so the agent can now approach that homeowner, offer his or her services, and have a much higher probability.”
Sirosh said Compass agents have a 94% higher chance of winning a potential listing they target with AI than not. Agents can supposedly price the home more exactly and target marketing more specifically.
For those searching to buy a home, all the data available can also help them to find exactly what they’re looking for, rather than touring house after house.
Using Compass’ AI, they can evaluate the price of their property in comparison with other properties in the market, search for specific types of homes in ultra-specific locations, input desired square footage of indoor and outdoor spaces and then get immediate alerts when something hits the market.
Zillow recently upgraded its popular home price ″Zestimate,” claiming it now uses neural networks, or machine learning comparable to how the brain works.
“In the case of the Zestimate algorithm, the neural network model correlates home facts, location, housing market trends and home values. As a result of this update, the Zestimate can now react more quickly to dynamic market conditions, providing homeowners with a more accurate estimate [prediction] of a home’s current value,” according to a Zillow release.
The company is now incorporating this new learning into its direct cash-offer homebuying business, Zillow Offers.
So far, the Zestimate is an initial cash offer on about 900,000 eligible homes across 23 markets.
“With this latest update and increased Zestimate accuracy, the number of homes eligible for a cash offer will likely increase by 30%,” according to the release.
AI is not doing anything that traditional research couldn’t accomplish, but it does accelerate the process dramatically, which in a fast-moving and ultra-competitive market, is crucial to these businesses.
“AI allows you to go to the self-driving dimension, which is AI outsources the heavy lifting that’s associated with a real estate transaction: the complex data, compliance, the paperwork, the finding of the home, the negotiation, the offers. I think that really makes a transaction go much faster. It is simpler, and it’s often cheaper,” said Sirosh.
With this speed, he said, artificial intelligence can conquer the most human component of any real estate transaction: stress.
source: cnbc
