The degree to which an AVM or cascade tends to overvalue or undervalue subject properties. Analysts quantify an AVM’s bias by calculating the mean or median valuation error.
Related Articles:
- Setting the Record Straight on AVM Testing MethodologiesThis op-ed offers an affirmation of the core tenets of what is becoming the industry-standard testing framework: a data-driven testing methodology grounded in sound and prudent validation principles. While Veros challenges this approach, the broader AVM ecosystem—including regulators, lenders, and nearly all major AVM providers—have embraced a process that prioritizes objective, real-world performance measurements over now antiquated methods allowing for data leakage into the Automated Valuation Model.
- Feds to Lenders: Take AVMs SeriouslyRegulators are signaling that they are going to be looking at AVM testing. They are focused on valuation discrimination. This represents a change in the focus on AVMs and the need for all lenders to focus on AVM validation to avoid unfavorable attention.
- Introducing PTM™ – Revolutionizing AVM Testing for Accurate Property ValuationsAVM testing is broken and has been for some time, which means that we don’t really know how much we can or should rely on AVMs for accurate valuations. AVMetrics is proud to unveil our game-changing Predictive Testing Methodology (PTM™), designed specifically to circumvent the problem that is invalidating all current testing.
- Using Appraised Values vs. Arm’s-Length Transactions for Testing AVMsUsing appraisals seems like a great way to get more benchmarks for testing AVMs, and since AVMs and appriasals are trying to do the same thing: predict sales prices, it seems intuitively appealing. However, there are some fundamental problems with using appriased values to test AVMs. Appraised values are subjective and inconsistent, and they introduce bias and compound errors. This article explains why arms' length transactions are the only appropriate way to test AVMs.
- Why AVMetrics’ Fair Housing Methodology Surpasses Vendor ApproachesVendor-published fair housing analyses represent early efforts to evaluate AVM bias, but they're inherently limited by their self-assessment nature. Each vendor tests only their own model and typically concludes little bias exists. AVMetrics' independent methodology conducts standardized, national testing across 700,000-1M quarterly transactions using Standardized Mean Difference metrics—delivering the regulatory-grade evidence lenders need to demonstrate compliance with new Interagency AVM Quality Control Standards