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Automated Valuation Model (AVM) – Examples of Uses of Big Data Software in Real Estate
- We will introduce the definition of the Automated Valuation Model.
- Big Data in Real Estate.
- Who really uses AVMs? Companies that incorporate AVMs into their work.
Nowadays, however, with AI swiftly overtaking many industries with its incredible streamlining capabilities, it’s little wonder that it’s been making an impact on the real estate industry as well. This takes the form of an AVM, or Automated Valuation Model, and Big Data. Let’s take a look at how these developments in AI have changed the face of real estate as we know it.
Before introducing AI, this was the only means of appraisal, and even today, it is still being used in tandem with AVM. The main idea behind the manual valuation process is quite simple – a real estate agent personally evaluates the worth of a building using physical inspection. They do this by looking at every part of the building, its location, the state of the market at the time of the appraisal, etc. All of these factors are analyzed and collected. While this data is analyzed more subjectively, if only because it’s performed by a human being, meaning that there may be a slight margin of error in human-provided sales prices compared to the ”real value” of a given building.
What is an Automated Valuation Model?
An AVM is a tool designed to perform the same function that manual appraisals do – establish the value of the building. To get that kind of valuation, they use historical databases that contain similar transactions. Of course, since the context changes over time, they also take the present physical infrastructure into account to get a more or less objective estimation. While these tools are quite effective, the industry has been taking its sweet time to adopt them, as humans are still considered cheaper and more reliable alternatives.
This looks like it may be changing shortly, however, because AVMs rely on Big Data, which means that their potential for making accurate, reliable valuations in the future far surpasses that of man.
Big Data based Software in Real Estate
All that being said, AVM still has a lot to offer even today. Many real estate agents or proptech companies, major financial institutions, and mortgage lenders utilize the services of AVM providers to boost their performance. The reason for this is quite simple: AVMs offer incredible accuracy a much more comprehensive coverage, and they streamline the process immensely, making it much less time-consuming.
AVMs utilize a hedonic model in their algorithms and a repeat sales index, which helps make the price estimate much more accurate. A good AMV will have access to all information relevant to the property in question, such as its sales history and sales data for other similar buildings. This process’s effectiveness depends on the data used, as only high-quality data can really be considered reliable and representative. However, it’s important to note that an AVM cannot simply physically enter the building to perform the evaluation, which in this case gives humans the edge, as they may spot faults that are otherwise undocumented in the data.
Automated Valuation Models have more uses beyond that. However, they can be used as added support by mortgage lenders for equity loan cases. They’re a great aid in credit risk management, as they provide another layer of evidence of the building’s state that may otherwise be put into question, improving the general confidence score regarding a given piece of real estate. It’s also important to note that AVMs aren’t exclusively used to value residential buildings.
Who uses AVMs? Let’s explore real market examples.
An increasing number of real estate companies worldwide are using AVMs, revolutionizing the industry as we know it. With more specialists employing these technologies, the AI systems used only have more room to grow. Here are some of the most prominent companies that incorporate AVMs into their work.
Zillow is a Seattle-based company that utilizes AI for digital photo evaluation as a basis for property value estimates. Their technology is based on a neural network with millions of photos in its database, making it very reliable, with only a two-per cent median error rate in terms of property value prediction.
A New York City-based company with ambitions to expand its horizons to other cities in the future uses AI for fact-checking apartment buildings, comparing various facts listed in the listing (e.g. size, amount of light) to the physical reality.
This San Francisco-based agency uses AVMs to estimate a home’s value in the present accurately and predict how it might change in the future. To achieve this, the AI draws on a database of over 40 years worth of housing sales data from all around the US. The estimates can get very detailed, taking into account things as specific as back porch views.
While AVMs are still in the process of making a name for themselves in the realm of real estate, it seems inevitable that, as Big Data expands and algorithms improve, that human real estate agents will rely more and more on them. The results they provide are already apparent even today, serving to streamline the process greatly. The few holes in their data, such as the current state of the building, may soon be filled with better access to data or even just better integration into the process of human appraisers.
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