The Challenge of AVM Testing in Quality Control
Automated Valuation Models (AVMs) have become a cornerstone of the appraisal quality control process, with many lenders and Appraisal Management Companies (AMCs) implementing what is commonly known as the “15% rule.” Under this framework, if an appraised value falls within 15% of the AVM estimate, the appraisal undergoes only a cursory review. Conversely, variances exceeding 15% trigger more thorough scrutiny or require review by another appraiser.
While this approach offers operational efficiency, it fundamentally misunderstands the distinction between precision and accuracy. This article examines why using appraisals as benchmarks for AVM testing creates a dangerous circular logic and proposes a more robust methodology centered on actual sale transactions.
Understanding Precision Versus Accuracy
Comparing AVM values to appraised values measures consistency—or precision—not accuracy. This distinction is critical yet often overlooked in the industry. While understanding the consistency between different valuation methods has operational value, particularly for ensuring that credit decisions are based on reliable estimates regardless of methodology, it serves a fundamentally different purpose than accuracy testing.
True accuracy in property valuation refers to how closely an estimate reflects the actual market value at a specific point in time. Market value, regardless of the valuation method employed, is universally defined as the most probable price negotiated between a willing buyer and seller in an arm’s length transaction. Therefore, the only meaningful measure of accuracy is the comparison to the actual negotiated sale price—the endpoint of the price negotiation process.
The Circular Logic Problem
The practice of using appraisals as benchmarks for AVM testing raises a fundamental question: Are we testing whether the model provides an accurate value consistent with actual sale prices, or merely a precise value consistent with appraisal estimates? This distinction has significant implications.
If AVMs tested against appraisals are mistakenly labeled as “accurate” rather than simply “consistent with appraisal estimates,” the quality control process becomes streamlined in a potentially dangerous way. More appraisals pass through without complications or delays from further review, creating a self-reinforcing cycle. This circular process—using AVMs in quality control to validate appraisals while simultaneously using appraisals as benchmarks to test AVMs—is fraught with risk and undermines the integrity of both valuation methods.
The Critical Role of Blind Testing
Determining the accuracy of any valuation estimate requires blind testing—the property’s sale price must be unknown when the estimate is produced. While implementing blind testing for appraisals presents significant challenges due to USPAP standards requiring appraisers to review and consider the terms of sale contracts, AVMs can and should be tested blindly with relative ease.
Most AVM vendors already conduct blind testing routinely as part of their quality assurance programs. This process allows modelers to understand model accuracy before a sale price becomes known—a critical capability for calibrating models and improving their predictive accuracy.
The Importance of MLS Data Suppression
The blind testing process must extend to MLS data, particularly listing prices. While listing prices occasionally match final sale prices, they more typically represent the starting point of buyer-seller negotiations. However, the listing price itself is not arbitrary—considerable analysis has already been completed to determine it.
Real estate professionals conduct thorough studies of the property, neighborhood, and relevant market activity—many of the same activities required for property valuation—before establishing a listing price. When AVMs have access to this information, they gain a significant advantage that may not reflect their true predictive capabilities. Therefore, proper testing must ensure that listing prices remain unknown when estimates are produced, maintaining the integrity of the blind testing process.
MLS data suppression also aligns with real-world use cases. In prominent AVM applications such as mortgage refinancing or home equity loans, the properties serving as collateral are rarely listed on MLS. Most lenders actually prohibit refinancing properties that are currently or recently listed. Testing AVMs without MLS data therefore provides a more realistic assessment of model performance in actual lending scenarios.
Regulatory Guidance and Compliance
The breadth and scope of AVM testing—including methodology selection and resource allocation—must be tailored to each institution’s unique circumstances. Regulatory guidance provides flexibility for organizations to demonstrate compliance within the context of their specific risk assessments.
While no explicit prohibition exists against using appraisal values as benchmarks, the Interagency Appraisal and Evaluation Guidance offers clear direction in Appendix B: “To ensure unbiased test results, an institution should compare the results of an AVM to actual sales data in a specified trade area or market prior to the information being available to the model.” This affirmative statement strongly supports the use of sales transactions as the foundation of AVM testing methodology.
Conclusion: Building a Robust Testing Framework
The distinction between measuring precision and accuracy in AVM testing is not merely academic—it has practical implications for lending decisions, risk management, and regulatory compliance. While comparing AVMs to appraisals may offer insights into consistency between valuation methods, it cannot and should not be mistaken for accuracy testing.
A robust AVM testing methodology must incorporate the following core principles:
• Use actual sale transactions as the primary benchmark for accuracy testing
• Implement truly blind testing protocols that exclude sale prices during estimate generation
• Suppress MLS listing price data for the benchmark property only to ensure unbiased testing. All other MLS-derived information—such as property characteristics, comparable sales, and broader market metrics—should remain fully available and not suppressed.
• Recognize the different purposes served by precision and accuracy measurements
As the regulatory guidance makes clear, institutions have the flexibility to design testing programs that suit their specific needs and risk profiles. However, this flexibility should not obscure the fundamental requirement: AVM testing must measure actual predictive accuracy against real market outcomes, not merely consistency with other valuation estimates. Only through rigorous, unbiased testing against actual sale prices can institutions truly understand and rely upon the accuracy of their automated valuation models.