The SFR Market: Tech and Big Data
- Big data expedites SFR sales, especially for large volume buyers.
- Emotional intelligence or the human touch is still essential in real estate deals.
- Single-family rental data still needs to be better organized.
Tech and big data used in selling property go beyond what most people can comprehend or process. However, real estate purchasers readily use information digested and organized by artificial intelligence and machine learning. At an industry talk, Jack Ryan, CEO at Rex, said his company bypasses the MLS, using big data, artificial intelligence and social media to connect buyers to property. Rex lists properties online on sites such as Zillow and Trulia. Today, 90% of home shoppers start their searches on the internet. But there’s still an emotional element to real estate. Just think about the homes where you’ve lived—and putting a price tag on them. So, what are the appropriate roles for AI and people in real estate transactions these days?
The Efficiency of Technology
Big data is driving up ROI. Real estate decisions rely upon millions of data points, Ryan commented. As one example, he noted with property sales, “In Texas, near the highway is a good thing to say. In California, it’s a bad thing to say.” Artificial intelligence can rapidly assess facts and figures that lead to accurate financial determinations. Algorithms can process vast amounts of data to compute the economic value of a home. Computers can crunch data far more efficiently than humans.
“You can’t do it from the human perspective,” Ryan said. “Human intuition will usually get overwhelmed by big data.”
Sean Tierney is the vice president of sales at Entera. Based in San Francisco, his company is a residential real estate platform that relies on machine learning. Currently, they are focusing on institutional investors. Tierney emphasized when a client is looking to buy 1,000 homes a year, time is of essence. “You have to be very laser-focused when you’re buying thousands and thousands of homes,” he said.
But he added transactions depend on who are the buyers and the sellers.
People Skills in Behavioral Finance
Machine learning can pick up quantitative facts about populations. Nonetheless, humans with emotional intelligence are still a crucial part of the equation. Unlike algorithms, humans can get to know the people who live in close proximity to the property.
Soft skills in understanding behavioral finance are still critical in the family housing industry. Residential deals can be emotionally fraught transactions for buyers or sellers, Ryan noted. “Oftentimes, people need to hold their hands. And that’s what humans do best.”
Tierney said transactions can have psychological associations. For example, just say 40 years ago, a father gifted stock to his son. As an adult, the son may now find it emotionally difficult to sell the stocks. However, with financial economics, one would instead focus on profits and losses.
A computer can calculate what property is worth down to the penny. However, an owner could fear losing money. Ryan described how a property owner could feel limits on options, being nervous about an uncertain job situation. That’s when humans with negotiation skills come into play. All companies need people to work together, regardless of individuals’ capabilities and the value of tech and big data.
Single-Family Rental Tech Challenges
The multifamily industry has more than 60 years of experience and data. George Aplicano, the owner of CashNowHomes, stated there needs to be greater collaboration in the single-family rental sector. The National Home Rental Council has acknowledged this, promoting greater compatibility in real estate technology.
Specifically, experts agree the industry lacks standardization of data points. There are challenges in defining acquisitions. Even some basic terms, including cap rates, can differ in definitions. Plus, tech companies store data in multiple ways to suit clients’ separate needs.
Companies could agree to organize certain pieces of basic information in consistent ways. For example, with IRS W-2 forms, each box is allocated to the same type of data. Establishing this type of standardized, structured data would increase the ease and efficiency in deals, lowering consumer prices.
The panel discussion, “Acquisitions & Dispositions: When to Use Technology and When to Use Property” was part of the IMN SFR Forum (West), held in December in Scottsdale, AZ. Listen to Arbor’s audio interviews on the conference. The first Q&A features a discussion of the conference highlights including SFR trends and investment opportunities. The second recording is a post-event wrap-up, covering the fix-and-flip market, bridge financing and more proptech. You can also contact Arbor today to learn more about SFR portfolio solutions and Arbor’s SFR portfolio loans.