Time marches on, and the world keeps changing all around us. With the economic model currently in place, industries can rise and disappear in the blink of an eye. Still, a few of them have been around for so long and become so ingrained in our society that it’s hard to imagine them going away. And yet do they stay the same?
Real estate is one such aspect of reality that has been around for, effectively, an eternity, and it’s safe to say it isn’t going anywhere. People will always need homes, property for their businesses, or other venues as too many aspects of our lives rely on them.
In turn, real estate mainly relies on property valuations. Property value is a rough representation of the benefits an owner of a given property receives. These benefits are generally long-term and can be very robust, which means that the process of valuation can be pretty involved. Traditional valuations have required a lot of attention from experts in the field.
As is the case with many other aspects of life, technology – and AI in particular – has introduced many clever solutions to the field of real estate. In this particular example, these solutions come in the shape of AVM, or the Automated Valuation Model.
AVMs – How They Work and Why They’ve Flipped Real Estate on its Head
Automation seems to be the way of the future, and that’s exactly what AVM does for real estate, as the name itself suggests. Through the use of large databases of existing properties and transactions, combined with modelling – either statistical or mathematical – AVM can efficiently calculate real estate values.
That’s the raw definition. What this entails for those working within the industry is a valuation process that’s not only much faster but also more efficient than the manual variant. With access to public records, while utilising machine learning, AVM can take into account a variety of the property’s physical attributes, such as its size, room count, materials, location, combine that with its historical pricing, to arrive at a property value that’s more accurate than any manual valuation
could ever get.
Thanks to big data, as well as the sheer efficiency of machine learning algorithms, the biggest hole in manual valuation, that being a human error, can be eliminated. Add to that the reduced manual workload, the amazingly reduced time to carry out the process, and you get an incredible reduction of costs.
AVMs to Look Out For
Up until now, we’ve been talking about AVMs like they’re one monolithic structure, but there is, of course, an entire smorgasbord of solutions for realtors out there. Here’s a list of some of the most prominent ones.
Zillow
Zillow is a name that’s pretty much synonymous with AVMs. If someone knows about AVMs, they know about Zillow. Based in Seattle, they rely on AI to handle their digital photo evaluation. With a staggering number of photos in their neural network, they can handle property value estimates with a margin of error as small as 2%.
CoreLogic
CoreLogic may not have many options for direct consumers, but realtors are familiar with CoreLogic’s RealAVM. The AVM has access to public records, making evaluating the property’s pricing based on its physical features and history quite easy. Additionally, it showcases a range and confidence score for even better quality data.
HouseCanary
One of the current biggest competitors to Zillow, HouseCanary uses a database of housing sales data from around the US that dates back over four decades. With an incredible amount of detail to their data, such as back porch views, HouseCanary can make very accurate estimates for both the present and future.
Realtor Property Resource RVM
An AVM made specifically with Realtors in mind. RVM” stands for Realtors Valuation Model, encompassing the company’s M.O. in a nutshell. With access to a robust database, listing tools, estimates, and CMA functions, it’s a great tool for realtors who want to take the initiative in the process.
Homesnap
Intended to be used by both agents and buyers, Homesnap not only uses reliable data for its valuations but also provides potential buyers with the same information as the agents receive.
Not Just Homeowners
While AVMs used to be strictly the domain of home property, they have since spread into the commercial sector as well. The valuation process for those slightly differs from residential real estate, being more complex and demanding more labour. Aside from the preliminary valuations and portfolio present in residential real estate valuation, there is also the addition of collateral assessments, risk management, and various other factors that don’t exist when the buyer is a simple homeowner.
AVMs for commercial property operate on a similar principle, with simply more factors being taken into account. Alongside the history of the building, other aspects relevant to the specific building will be calculated, with the ultimate value hinging greatly on how profitable the property will be for the potential buyer, as commercial clients have different needs than private owners. Companies offering commercial AVMs so far have been few and far between, but it is absolutely a growing market that is fated to see growth shortly.
It’s also important to note that there is yet another type of buyer that greatly benefits from AVMs: investors and lenders. For those, time is always of the essence, and any delay and human error can cause their revenue to plummet, so third-party evaluators are always risky. Luckily, as we’ve already established, AVMs can significantly reduce both the time necessary to perform accurate valuations, but also the margin of error.
Conclusion
The situation is clear: AVMs have arrived, and they’re here to stay. They’ve thoroughly revolutionised the real estate industry and then some. Serving as another example of just how much good implementation of machine learning and big data can change an entire industry’s landscape, AVMs can act as a face of time and cost optimisation across all industries, and a promise of even more impressive things to come.
