What is the RPS Automated Value Assurance (AVA)
The data-driven Automated Value Assurance (AVA) analysis tool examines the accuracy of appraised values and supporting information to help mortgage lenders, servicers, and insurers increase underwriting efficiency. RPS uses its industry–leading data analytics software combined with its national property database to apply 120 complex rules to over 500 appraisal report fields. Run on every appraisal report, the RPS AVA score helps answer the critical question: is the appraised value accurate and well supported?
Key Features
Better Decisions
Deliver meaningful information to review staff, to enable better and more informed decisions on outlier properties
Reduce Risk
Leverage objective, comprehensive information to better support internal due diligence processes consistently across all files.
Empower Staff
Empower staff and executives with information for better supported and more informed discussions with consumers, regulators and other internal stakeholders.
Better Compliance
Implement and maintain better frameworks for critically reviewing and effectively challenging the assumptions and methodologies underlying property appraisals, consistently and objectively.
Flexible Approach
Extensive Data Analytics: RPS applies 120 complex rules to 500+ appraisal report fields and includes analysis of comparables selection, adjustments, commentary, and the appraised value.
Proprietary Score: AVA generates a score out of 1,000 – the higher the number, the higher the accuracy – an easy and quick way to assess the accuracy of the appraised value.
Flags and Outliers: Outlier reports are flagged indicating where and why further report analysis may be required. Additional review can be done by RPS experts and/or your staff.
The AVA Report
- AVA Score: An easy, quick, and comprehensive way to assess the accuracy of the appraised value and report quality.
- Flags: Provide high visibility of what and why further investigation might be warranted for each section analyzed.
- Comparable Selection Analysis: AVA algorithms analyze comparables to ensure quality - proximity, value relative to subject. Comparables are compared to other potential properties to assess suitability.
- Appraiser Adjustment Analysis: AVA further analyzes line-item adjustments on each comparable property, or in the case of the cost-approach replacement items, relative to local neighbourhood averages and normal distribution bands.
- Appraiser Commentary Analysis: AVA uses machine learning models to parse and analyze appraiser comments to identify outliers and ensure that the commentary is aligned with other sections of the appraisal report.
- Value Comparison Analysis: AVA uses RPS value analytics to compare the appraised value to a machine learning automated value estimate, local market averages, and market trending data.
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