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Automated Valuation Model (AVM)

Automated Valuation Model (AVM)

What Is an Automated Valuation Model (AVM)?

An automated valuation model (AVM) is a term for a service that joins mathematical or statistical modeling with databases of existing properties and transactions to compute real estate values. The majority of AVMs compare the values of comparative properties at a similar point in time.

Numerous appraisers, and even Wall Street institutions, utilize these AVMs to value residential properties. Consumer-prepared AVMs additionally exist on property listing destinations like Zillow and Trulia.

How Do Automated Valuation Models (AVMs) Work?

AVM reports are driven by technology, including proprietary calculations, and can be acquired in seconds by lenders and agents. They normally contain both a hedonic model (a type of statistical regression analysis) and a repeat sales index, which are both weighted and investigated to create the price estimate. AVMs typically incorporate the tax assessor's value, all relevant data on the property being referred to โ€” like its sales history โ€” and an analysis of the sales of like-kind properties.

They are likewise used to support underwriting for mortgages and home equity loans, for refinancing choices, and to aid in loss moderation and credit risk management activities like marking-to-market of real estate holdings in institutional investment portfolios. While AVMs initially were utilized to value residential real estate, their utilization has expanded to different types, including commercial real estate.

AVM suppliers offer their services to different clients, including real estate agents and brokers, mortgage lenders, and major financial institutions. Leading AVM suppliers incorporate CoreLogic, the Federal Home Loan Mortgage Corp. (Freddie Mac), VeroVALUE, and Equifax. The public can utilize them through free consumer real estate destinations.

Zillow's famous electronic real estate valuation apparatus, Zestimate, is one notable type of AVM.

Advantages and disadvantages of Automated Valuation Models (AVMs) in Real Estate

Notwithstanding their broad use these days, AVMs spark some discussion, particularly over how they compare to traditional in-person appraisals.

Benefits of AVMs

The upsides of utilizing AVMs over physical appraisals are like those of any automated system over human exertion. Fundamentally, they save time, money, and exertion. They can make various estimations and examinations in a flash, and they don't have to physically drive out to see a property or comparative properties ("comps" being a key factor while evaluating and pricing a specific piece of real estate).

Each of this brings down the cost of esteeming a property or numerous properties. AVMs are especially valuable in evaluating the worth of a whole real estate portfolio. When set up, AVMs can be worked with little expense.

As well as being less expensive and quicker, calculations aren't subject to human blunder โ€” or malfeasance. As objective robots, they eliminate bias and subjectivity from the equation. In this manner, there's less risk of fraud or conscious mispricing โ€” in spite of the fact that, of course, computer programs can be hacked or controlled.

A 2017 conference paper, "Automated Valuation Models (AVMs): an exciting modern lifestyle?" by George Andrew Matysiak of the Krakow University of Economics, referred to different studies in tending to the qualities and the deficiencies of these models. "There is minimal hard fair-minded evidence on the precision of commercially accessible AVMs in the public domain," the paper noted. "In spite of high average exactness levels, statistically based valuations might be widely misguided and should be augmented by professional judgment."

Detriments of AVMs

For an AVM to function admirably, it needs high-quality data in enough quantity to be representative. That is where its weakness lies.

The most frequently refered to drawback against AVMs is that in determining value, they don't (and can't) factor in the genuine condition of the property. They just accept an average state, which might possibly be accurate. They can't note subtleties or varieties in the condition.

AVMs are great at examinations, yet consider the possibility that there is a deficiency of comparable real estate (comps) or conditional data on record. Hence, recently fabricated properties are particularly hard to value, and AVMs, being fairly strict, will quite often lack the creative mind to concoct something to act as comps. Also, on the grounds that an AVM works in view of known factors โ€” the historic record โ€” it passes up intangibles that can raise or lower an estimate.

At long last, an AVM can work with the data that it is given, and consistently the risk of data is being placed erroneously. Additionally, the data that it has probably won't be modern โ€” making AVMs questionable in quick changing real estate markets.

The Bottom Line

Major AVM suppliers promote their exactness, thorough coverage, and time savings. AVMs deal in averages. So they are especially effective where the property stock is extremely generic. In locales with a bigger scope of types and styles, they might be less accurate and helpful.

While their utilization is developing, AVMs have not replaced human valuation estimates, not least on the grounds that most mortgage lenders require a tweaked appraisal of a property to be carried out in person by a certified appraiser. Due to worries over their precision, some industry participants propose seeing outcomes from various AVMs as a method for getting a more complete picture and to increase confidence in their reports.


  • Automated valuation models (AVMs) are software-based pricing models utilized in the real estate market to value properties.
  • AVM suppliers incorporate commercial platforms like CoreLogic, Freddie Mac, and Equifax, as well as free consumer destinations like Zillow and Trulia.
  • AVMs are more efficient and predictable than a human appraiser, however they are likewise just as accurate as the data behind them, meaning they might be obsolete or mistaken.