AI in Property Valuation: The Most Consequential Algorithms You’ve Never Heard Of

Alex C. Engler is a Fellow at the Brookings Institution and an Associate Fellow at the Center for European Policy Studies, and teaches AI policy at Georgetown University, where he is an adjunct professor and affiliated scholar. Sylvia Brown is a graduate of Georgetown University’s McCourt School of Public Policy and works in social science research in Chicago. Shutterstock If we told you about an AI built on the latest foundation models that shapes multi-trillion-dollar markets and ‘walks’ through every home in the United States, would you say it was science fiction? Well, let us introduce you to Automated Valuation Models, or AVMs, invented a century ago.  AVMs are algorithmic systems that estimate the market value of properties, such as residential homes and commercial buildings. Knowing the sales price of a home is critical to lenders who make loans on the basis that, if they aren’t paid back, they can foreclose on, and then sell, the property. This is the basic idea behind much of housing finance, including mortgages and home equity loans, a market built on 41 trillion dollars of property value. It’s also become a key feature of online platforms, especially Zillow and Redfin, which use home price valuations to attract over 250 million monthly buyers, sellers and voyeurs to their websites. Traditionally, estimating the value of a property has been done by human appraisers, but over the past several decades, algorithms have taken on a larger role. Invented in the 1920’s, AVMs have been increasingly commercialized since…AI in Property Valuation: The Most Consequential Algorithms You’ve Never Heard Of