Appraising Atypical Properties: Understanding the New Data-Driven URAR
Explore the shift from legacy appraisal forms to the data-driven URAR (UAD 3.6), focusing on how 6 key data points define reports for typical & atypical properties.
Explore the shift from legacy appraisal forms to the data-driven URAR (UAD 3.6), focusing on how 6 key data points define reports for typical & atypical properties.
Hey fellow appraisers, John Anderson here. We've all been navigating the waves of change washing over our industry, particularly with the ongoing rollout of the Uniform Appraisal Dataset (UAD) 3.6 and the redesigned Uniform Residential Appraisal Report (URAR) by Fannie Mae and Freddie Mac. One of the most fundamental shifts is the move away from relying on specific form numbers (like the 1004, 1073, etc.) to define our reports.
Instead, the new dynamic URAR is driven by the data we collect about the property's characteristics. This is a significant change, moving us towards a more flexible and standardized system. While this brings many benefits, it also raises questions, especially when dealing with properties that never quite fit neatly into the boxes of the old legacy forms – what the GSEs are calling "atypical properties." This post will dive into how the new URAR structure accommodates these unique assignments.
Remember juggling different forms for different property types? A standard single-family needed a 1004, a condo unit a 1073, a manufactured home a 1004C, and so on. While familiar, this system had limitations. Properties with unique combinations of features often required extensive narrative explanations in addenda to clarify characteristics not adequately captured by the form itself.
The new UAD 3.6 approach retires these legacy forms for GSE purposes. The redesigned URAR is a single, dynamic report structure. Its content and layout adapt based on the specific data points entered for the subject property. This means the characteristics define the report, not a pre-printed form number.
So, how does the system know what kind of property it's dealing with if there's no form number? Based on the GSE guidance document, "Functioning without Form Numbers," six key UAD data points primarily drive the property type characteristics within the new URAR:
These data points, collected during the appraisal process, instruct the software on how to assemble the relevant sections and fields within the URAR output. You can see these fields clearly identified in the URAR Summary section (check the GSE examples like Appendix D-1 or the 'Functioning without Form Numbers' doc for visuals with Field IDs, or FIDs).
For the most common assignments, the transition is relatively straightforward. A standard detached single-family home, a typical attached condo unit, or a 2-4 unit property have clear correlations between the old forms and the combination of these new data points. The GSEs have provided mapping tables showing how legacy forms translate to these property characteristics.
The real advantage of the dynamic URAR becomes apparent when dealing with properties that previously caused headaches. The old forms often fell short for:
The new URAR, driven by those key data points, can represent these accurately without needing a unique form for every combination. Here’s how it works conceptually, based on the GSEs' 'Atypical Properties Mapping' guidance:
Construction Method: Site Built
, Project Legal Structure: Condominium
, and Subject Site Owned in Common: No
.Units Excluding ADUs: 1
and Accessory Dwelling Units: 2
.Construction Method: Manufactured
and Project Legal Structure: Condominium
.By accurately capturing these distinct data points, the system generates a URAR that reflects the specific nature of the property. This allows for greater consistency and reduces the reliance on lengthy addenda simply to explain the property type.
This shift emphasizes the critical importance of accurate data collection, particularly for those six key fields.
The retirement of legacy appraisal forms marks a significant step towards a modernized appraisal process. By leveraging a dynamic URAR driven by specific data points, the GSEs aim to improve consistency, flexibility, and data quality. For us appraisers, this means adapting our focus from form selection to meticulous data collection and understanding how property characteristics shape the final report. Embracing this data-driven approach, especially for those atypical properties, will be key to navigating the future of appraisal reporting successfully.