Automated Valuation Model for Appraisal Reliability Assessment
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Solution Overview
Problem
Financial entities face challenges in assessing the reliability of property appraisals, leading to potential misinterpretation and unnecessary reappraisals, as existing methods are burdensome and lack efficiency in determining appraisal accuracy.
Innovation Solution
A system and method for generating a Home Value (HV) Score, based on a model that evaluates information about borrowers, properties, and demographics, to indicate the likelihood of a faulty appraisal, allowing for more accurate assessment and targeted quality control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional appraisal methods are used, then property value assessment can be performed, but the process is burdensome and lacks efficiency in determining appraisal accuracy
Solution Approach 1:
The patent introduces an automated valuation model (AVM) as an intermediary system that generates independent property value estimates using algorithms and market data. This AVM acts as a mediator between the traditional appraisal process and the financial entity's decision-making, providing an objective benchmark to assess appraisal accuracy without requiring manual review of every appraisal.
Solution Approach 2:
The patent replaces the manual, mechanical process of reviewing appraisals with an automated computational system. The AVM uses computer algorithms to analyze market data, property characteristics, and sales comparisons, substituting human appraisers and reviewers with an automated system that can process valuations rapidly and consistently.
2Reliability
If financial entities order unnecessary reappraisals to verify appraisal accuracy, then appraisal reliability can be improved, but financial and administrative burdens increase
Solution Approach 1:
The patent implements a selective verification approach where the AVM is used to identify only those appraisals that fall outside acceptable value ranges or exhibit anomalies. Instead of reviewing all appraisals or ordering reappraisals for every case, the system performs partial verification only when necessary, reducing the number of reappraisals while maintaining reliability for problematic cases.
Solution Approach 2:
The patent establishes a feedback mechanism where the AVM's independent valuation is compared against the original appraisal, and this comparison feeds back into the decision-making process. When the AVM valuation is within an acceptable range of the original appraisal, the system provides feedback confirming the appraisal's reliability. When discrepancies exceed thresholds, feedback triggers targeted verification or reappraisal, optimizing resource allocation.
3Speed
If automated valuation models are used, then appraisal processing speed increases, but the ability to interpret complex appraisal scenarios may be reduced
Solution Approach 1:
The patent segments the appraisal review process into distinct functional components: the AVM handles routine valuation calculations and data processing tasks, while human experts focus on interpreting complex scenarios, unusual property conditions, and edge cases. This segmentation allows the automated system to operate at high speed for standard cases while preserving human judgment capability for complex situations.
Solution Approach 2:
The patent merges the strengths of automated valuation models and human expert judgment into a hybrid system. The AVM provides rapid, consistent valuations based on market data, while human appraisers and reviewers provide contextual understanding and interpretive judgment. The system combines these approaches by using the AVM as a first-pass tool that flags cases requiring human review, creating a synergistic workflow that achieves both speed and interpretive capability.
Data Source
AI summary
Systems and methods are provided for providing, based on a model, an indication that an appraisal value for a property is likely to be faulty. In one embodiment, a method includes receiving information representative of at least one of a borrower, a property, or one or more demographics, such that the received information corresponds to a date. The method determines a score based on the received information and the model, such that the score provides the indication of the likelihood that the appraisal value was faulty on the date.