The term Automated Valuation Model (AVM) describes a service that applies algorithmic and statistical estimates to calculate real estate values for the brokers. The AVMs utilize data of the currently prevalent comparable real estate values and transactions to arrive at a computer-generated value for a particular property.
AVM calculations use several factors such as title records, values of identical real estate, and comparable sales in a particular area. Many mortgage brokers, appraisers, and institutions use automated valuation models to assess property values.
Use of Big Data in the Automated Valuation Model and Its Applications
Many of the wall street financial institutions, mortgage brokers, and real estate agents, utilize the services offered by Automated Valuation Model (AVM) providers such as Vero Value, Freddie Mac, CoreLogic, and Equifax. Most major service providers proclaim and promote the speed, accuracy, and extensive coverage of their AVMs.
An AVM report usually employs a hedonic regression model and the repeat sales index to come up with a price projection. A hedonic regression model uses the qualities that influence the utility of the goods or services as independent variables. Technology and customized algorithms make the AVMs fast and accurate for the lenders.
The AVMs generally include all the relevant information on the concerned real estate, including the sales history, the value estimated by the tax assessor, and data from the sale of similar properties. A significant quantity of quality data is crucial for the optimum performance of the valuation model.
While originally valuation models mostly helped in evaluating residential properties, their growing applications now include commercial and other types of real estate as well. Some of the other AVM usages typically include their support in mortgage underwriting, loss mitigation, risk management, and refinancing.
How do AVMs Compare Against the Traditional Appraisals?
Mortgage lenders and institutions use AVMs to evaluate properties on account of their speed, ready availability, and affordability, in comparison with a regular appraisal. Having said that, there are mortgage lenders who are averse to using AVMs during the loan approval process. Let us find out some of the areas where an AVM can fall short and not capture some of the things that a formal appraisal can.
While the AVMs may fail to factor in some of the elements, a formal appraisal process takes these, and more, into account. An appraisal by a licensed professional takes longer and costs more, but provides the best picture of a property’s value.
Mortgage brokers and institutions can use an AVM in combination with a formal appraisal to eliminate loose ends and obtain a comprehensive input of a property’s value. They should initially use an AVM during the lending process to crosscheck the estimated value with the potential homeowner’s figures.
If the AVM estimate is close to the customer’s figures, a formal appraisal can be the next step to reassess and reconfirm the valuation. It is best to think of an AVM as a precursor to an appraisal.
How do AVMs Score Over the Traditional Valuation Methods?
Traditional property appraisal and valuation process have remained unchanged as far as we can think back. Comparison of the property to similar properties in the immediate area and comparison of transactions involving similar properties has been the benchmark in valuation.
Professional appraisers and mortgage underwriters do add certain other parameters including the build quality and maintenance of the property. But overall, Comparative Market Analysis (CMA) has undoubtedly been the bulwark of traditional real estate valuation.
Human Error in Traditional Valuation
Traditional valuations like comparative market analysis, unfortunately, have high human error rates. Research shows error rates of up to 16 percent for properties valued below one million dollars, with traditional valuation methods.
However, AVMs involve minimal manual processes which in turn translate into a lower error rate. The absolute error in automated valuation models is less than 4 percent for residential real estate and less than 6 percent for commercial properties.
In-built Bias in Traditional Valuation
Manual valuation processes have an in-built bias, like the degree of familiarity that the appraiser has with the property or the immediate neighborhood.
The client’s influence can also skew the comparative valuation. A home loan applicant may want a high valuation, while another homeowner may seek a lower valuation for the purpose of saving tax.
AVMs Save Time
Mortgage brokers, lenders, investors, and buyers are wary of the time taken in seeking a formal appraisal. There is a typical time lag of three to four weeks between calling for a manual valuation and getting a report. AVMs, on the other hand, require almost no time at all in generating reports.
Comparative Analysis Requires More Information
Traditional appraisal methods may fail to apply in submarkets that are too small to properly run a comparative market assessment. But there are sufficient data points to accomplish property comparison reports with AVMs.
AVMs are More Objective
With AVMs, the entire process of valuation is not only faster, more accurate, and less prone to errors, but also more objective since it is completely based on unbiased data.
Automation Valuation Models Poised for Expansion
Presently, AVMs are in their nascent stage in the real estate market. But with expansion in big data and constant improvements in proprietary algorithms, their usage will expand inevitably. Their benefits are apparent even today, and they are on the verge of further growth with more access to data and better integration into the appraisal process.
How You Can Integrate AVM into Your Business as a Mortgage Broker with Fundmore.ai
Big Data and Machine learning are constantly evolving and helping drive the growth in the mortgage industry. We can foresee these technologies developing at a rapid pace over the next few years, ushering in an era of faster speeds, higher efficiencies, and greater security.
Real estate appraisal is the foundation for the mortgage lending industry. A small improvement with automated valuation models can effect a powerful change. Big data is suited for AI-driven applications in the mortgage lending industry, as it lowers costs and human errors with increased automation.
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