Appraisals and ValuationsOpinionReal Estate

Real estate is a people business, but automation can help

AI, machine learning and computer vision can reduce appraisal bias

The news is filled with talk of real estate. Bubbles have that effect. We know through the work of people like Robert Shiller and others that “narratives” are indeed economic forces and that compelling narratives can move markets.   

In the U.S. real estate market, matters are of course more complex than mere narratives, but we do all know that constant hype adds to the buoyancy of markets, which then creates more hype. These virtuous loops are common in a variety of areas of the economy and real estate is no exception. 

A lot is at stake. The U.S. residential real estate market is valued at about $40 trillion in aggregate. Real estate/housing is the bellwether for the entire economy and houses represent the typical family’s most important financial decision. So much of life radiates from both the location and the valuation of the house a family occupies.   

This twin importance — on both the macro and the personal level — draws a great deal of interest in this marketplace and its various offshoots. Still, the residential real estate ecosystem is complex, even opaque to many. Homebuyers and sellers contend with a variety of entities — banks, insurance companies, mortgage servicers, appraisal companies, title providers, agents, brokerages, and even real estate marketers— and the process can be labyrinthine to even those who have gone through it before.  

Technology plays a big role. So too does trust — usually manifested in the relationship between a buyer/seller and a real estate agent. For those who choose not to work with agents, the trust must be transferred to the technology platform or other form of “automation” that is used in the process. 


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It’s worth reiterating the importance of trust. As mentioned, much is determined by the location and valuation of houses. The residues last for generations. Houses represent a major part in generational wealth transfer and inheritance and also play a major, and persistent, role in determining life conditions during the owners’ lifespan. What schools do the kids go to? How safe is my family? Who are my neighbors? How much wealth have I amassed? When can I retire? All of these fundamental questions radiate from what can appear to be a mundane question: What house do I buy? 

With so much riding on this, it is important to locate the most relevant elements when determining whether to buy or sell a house. Of these, one stands tall: valuation. What is the house worth? What does the house cost? These two questions are at the center of all things residential real estate. 

Such a simple set of questions with such complex answers. Many variables impinge on the value of a house. There are the usual ones: size, age, location. There are important ones that are hard to capture in “macro-statistics” — the interior condition of the house being a major one. There are external factors that weigh heavily, alluded to in the first paragraph above, that have to do with momentum, fashion, and the narrative/desirability of a particular neighborhood over another. And so many more parameters as well. 

Thus, the simple questions have complex answers. As real estate experts will tell you, the process of valuing not only a house,  but large swaths of houses, even all houses in the U.S., requires deep technology insight, incredible ability to extract, transform, and ingest data, and a process by which you can query data with ease and speed. Not only are there a huge number of variables to understand, but also a variety of “forms” the data comes in — spreadsheets, pictures, and so on.  

The task is best suited for advanced technologies, collectively referred to as AI and machine learning. Add to this computer vision and you get the right cocktail for which the industry has long waited and which, more importantly, consumers and all parts of the real estate ecosystem deserve. 

In a $40 trillion market that constitutes most families’ most important investment, “good enough” is not in fact good enough. 

There is more too than simple economics. There is also a matter of, to put it clearly, fairness and justice. House valuations come into play at crucial times in the transaction process; they not only bookend the entire journey but also crop up during the time of “appraisal.”  

We hear shocking stories of racial discrimination and a variety of other ills during the appraisal process.  While people are prone to massive bias — as with the case of appraisers who suggested that an African-American woman’s house was worth half of what it was appraised for when she had a white friend pose as the stand-in owner.  

Technology has biases too but only to the extent that they are algorithmically coded into the outcomes. As such, “black box” AI, which is to say completely opaque AI, needs to be replaced with an AI that is explainable and deconstructable so that biases can be identified and done away with. 

The value of a house is a number of incredible importance and is one that is invoked often in real estate and in personal financial planning. Still, while it is given heed by many parts of the real estate ecosystem, few elements of that ecosystem demand simultaneous precision and depth. This is a mistake, and one that can have massive consequences for individual families, entire neighborhoods, and for the economy as a whole. Settling won’t do anymore.  

In the recent “Gathering of Eagles” conference, a particularly high-powered set of panelists all agreed that real estate is a “people business.” While this might be true at some level, there is nothing that suggests that people need to perform every single function in the multiple and complex journeys of house buying and selling, nor that they can be relied upon to offer unbiased and fair valuations without fear or favor.   

Technology is not a panacea, nor will it ever be.  But to use the tools that have been painstakingly developed over decades to enhance what is absolutely a people business is the smart thing to do. And it can help reduce bias, increase fairness and generate economic bounty for the entire real estate ecosystem. 

This column does not necessarily reflect the opinion of HousingWire’s editorial department and its owners.

To contact the authors of this story:
Romi Mahajan at [email protected]

Jeremy McCarty at [email protected]

To contact the editor responsible for this story:
Sarah Wheeler at [email protected]

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