The news is full of real estate talk. Bubbles have this effect. We know through the work of people like Robert Schiller and others that “narratives” are indeed economic forces and that compelling narratives can move markets.
In the US real estate market, things are, of course, more complicated than just stories, but we all know that constant hype increases the excitement of markets, and then creates more hype. These useful hinges are common in a wide variety of industries, and real estate is no exception.
There’s a lot at stake. The US residential real estate market is collectively valued at about $ 40 trillion. Real estate / housing is the benchmark for the entire economy, and houses represent the most important financial decision of the typical family. So much life comes from both the location and the appreciation of the home the family lives in.
This double importance – on a macro as well as a personal level – is generating a lot of interest in this market and its various offshoots. However, the residential real estate ecosystem is complex and even incomprehensible to many. Home buyers and sellers face a variety of organizations – banks, insurance companies, mortgage companies, appraisal companies, copyright holders, agents, brokerage houses, and even real estate sellers – and the process can be confusing, even for those who have gone through it before.
Technology plays a big role. It is the same with trust, which usually manifests itself in the relationship between a buyer / seller and a real estate agent. For those who choose not to work with agents, trust must be transferred to the technology platform or other form of “automation” that is used in the process.
It is worth re-emphasizing the importance of trust. As mentioned, a lot is determined by the location and value of the houses. The remnants persist for generations. Homes play an important role in the transmission of wealth and the inheritance of generations, and also play an important and permanent role in determining the living conditions throughout the life of the owners. What schools do the children go to? How safe is my family? Who are my neighbors? How much have I saved up? When can I retire? All of these fundamental questions come from what may seem like a trivial question: Which house should I buy?
With so much focus on this, it is important to identify the most important elements when deciding whether to buy or sell a home. Of these, one stands out: evaluation. How much is the house worth? How much is the house worth? These two questions are at the heart of everything related to residential real estate.
Such a simple set of questions with such complex answers. Many variables affect the value of a home. There are the usual ones: size, age, location. There are important ones that are difficult to capture in “macrostatistics” – the internal state of the house is the main one. There are external factors that are of great importance, mentioned in the first paragraph above, which have to do with the impulse, fashion and narrative / desirability of one area over another. And many more parameters.
Thus, there are complex answers to simple questions. As real estate experts will tell you, the process of appraising not just homes, but large tracts of homes, even all homes in the United States, requires a deep understanding of technology, incredible ability to extract, transform and receive data, and a process that you can query data with ease and speed. It is necessary to understand not only the huge number of variables, but also the many “forms” in which data comes in – spreadsheets, images, and so on.
This 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 that the industry has long been waiting for and, more importantly, that consumers and all parts of the real estate ecosystem deserve.
In the $ 40 trillion market, which is the most important investment for most families, “good enough” is actually not enough.
This is more than simple economics. It is also, to be clear, fairness and fairness. Home appraisal plays an important role at crucial points in the transaction process; they not only complete the entire journey, but also arise during the “evaluation.”
During the certification process, we hear shocking stories of racial discrimination and a host of other troubles. Although people are prone to massive bias – as in the case appraisers who suggested that an African American woman’s home was worth half of what it was valued for when she had a white friend posing as a replacement owner.
Technologies also have biases, but only to the extent that they are algorithmically encoded in the results. Thus, the AI of the black box, that is, a completely opaque AI, needs to be replaced by an AI that can be explained and disassembled so that bias can be identified and eliminated.
Home value is incredibly important and is often mentioned in real estate and personal financial planning. However, while many parts of the real estate ecosystem pay attention to this, some elements of this ecosystem require both precision and depth at the same time. This is a mistake that can have serious consequences for individual families, entire areas and the economy as a whole. There will be no more settlement.
In the recent “Collecting eagles “, especially influential panellists agreed that real estate is a “business of the people”. While this may be true on some level, there is nothing to suggest that people must perform every single function in the many and complex processes of buying and selling a home, or that they can be relied on to offer impartial and fair evaluations without fear or fear. service.
Technology is not a panacea and never will be. But using tools that have been painstakingly developed over decades to improve what is purely human business is a smart move. And it can help reduce bias, increase equity, and provide economic benefits to the entire real estate ecosystem.
This column does not necessarily reflect the views of the HousingWire editorial team and their owners.
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Romi Mahajaran, firstname.lastname@example.org
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