New! Click here to access the current value acceptance + property data service provider list.

 

Value acceptance + property data has arrived

This new option reduces cycle times and may reduce borrower costs, promotes safety and soundness by obtaining a current observation of the subject property, and provides operational simplicity and certainty at time of loan application.

Fact Sheet  Lender Checklist  Service Provider Checklist

 

The modern valuation spectrum

Fannie Mae is on a journey of continuous improvement to make the home valuation process more efficient and accurate. We're transitioning to a spectrum of options to establish a property’s market value, with the option matching the risk of the collateral and the loan transaction. The spectrum balances traditional appraisals with appraisal alternatives.

Resources

 

 

Glossary of terms

Uses data and a modeling framework to confirm the validity of the value/sale price. For purchases and refinances; especially well-suited for low-risk refinances when the subject and market data is abundant.

Property data is collected by a trained and vetted third party (real estate agent, insurance inspector, appraiser, etc.). Lender reviews data and warrants property eligibility.

Consists of a full interior and exterior inspection of the subject property. The data collection can be performed by a trained and vetted third party.

Property data collected by a trained and vetted third party (real estate agent, insurance inspector, appraiser, etc.) is passed to an appraiser to perform an enhanced version of a desktop appraisal. For loans that do not qualify for value acceptance or do not have reliable prior observations of the subject property.

Appraiser completes the appraisal without physically inspecting the property, using data from various sources (agents, homeowners, MLS, tax records, etc.). Best suited for purchase transactions.

Appraiser collects the property data and completes the market analysis required for the appraisal. For complex property types or situations where data is sparse.