What Algorithms Are Doing for the Real Estate Industry

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At its most basic, an algorithm is a sequence of hard-and-fast instructions designed to solve a problem. A core tenet of computation, algorithms allow a computer to execute complex tasks efficiently and consistently following a predetermined set of steps.

Recently, algorithms have become incredibly sophisticated due to the application of artificial intelligence and machine learning. The marriage of complex algorithms and big data has also churned out several insights that no one imagined possible before.

That’s especially true in real estate. While the real estate industry was initially reluctant to embrace AI and algorithms (or any technology, for that matter), it has softened significantly in recent years. Now, you’ll find hyper-intelligent algorithms wherever you look in real estate.

This article explores three examples of algorithms in the real estate industry.

Connecting Consumers with Their Perfect Real Estate Agent

When Nobul first launched in 2017, it caught a great deal of attention from the industry. Consumers loved it because it foisted transparency and accountability on the real estate process. But some practitioners were unsure because, well… see the reason above.

The company uses a proprietary AI-led algorithm to comb through conventionally hidden information about agents – transaction histories, commission rates, verified reviews, etc. – then provide recommendations for relevant agents based on a “match score.” Agents can then compete for the consumers’ business with competitive rates and services.

“We’ve massively simplified the whole process,” says founder Regan McGee. “People think buying and selling real estate is complicated, but that’s a way for agents to justify their fees.”

Home Valuations in Dynamic Markets

As CNBC points out, most of the information you need to evaluate a home is contained within public land records, title documents and selling price history – but until recently, processing that data was burdensome and time-consuming.

Then AVMs came along (automated valuation models), computer algorithms designed to extract as much public information as possible to estimate a home’s value. Unlike the manual method, algorithm-driven AVMs are instant, working on the latest data to provide accurate valuations in even the most dynamic markets. This approach gave rise to a slew of AVM services – the most popular being Zillow’s “Zestimate.”

Most experts caution that these valuations should be used for illustrative purposes only (a professional evaluation is still best practice). Still, there’s no doubt that algorithmic AVMs are a leap forward for consumer empowerment and access.

Buying Up Investment Opportunities

For an example of how companies use algorithms to pounce on investment opportunities, let’s rip a page from recent headlines. Recently, the New York Times profiled WeWork, the sublet startup poised for collapse after it downplayed losses to investors. The company was once lauded for using sophisticated algorithms in its location acquisition, but the Times article calls its practices into question.

Experts contend that the company, and investment companies like it, are on shaky ethical ground – feeding data from social media and geotagging through an algorithm to determine the newest areas ripe for gentrification. These companies gobble the real estate up, spurring demand and lowering supply.

In the right hands, these algorithms can be a potent tool for good-faith investors. But it’s important to be honest about how algorithms can also be misused in real estate.

As computers play an increasing role in the brick-and-mortar industry, artificial intelligence and algorithms will continue to “solve the problems” they’re programmed to solve. Some problems, like the lack of transparency in agent-client relationships that Nobul addresses, deserve solutions. Other problems, like how to game real estate investment at the expense of common consumers, are less deserving of praise. As real estate tech makes clear, algorithms are only as beneficial as the people behind them.