Freddie Mac Home Value Explorer (HVE)
For 12 years Freddie Mac has effectively employed AVMs internally for its own risk and portfolio management. Freddie Mac's
Home Value Explorer (HVESM) streamlines the lending process by cutting the collateral valuation cycle down to seconds,
while saving hundreds of dollars on each transaction.
HVE
- Supports many typical lending functions including
- Processing second mortgages
- Home equity loans and home equity lines of credit
- Loss mitigation
- Supports processes related to purchase, sale or construction of homes.
- Provides consumers with a better understanding of the value of their home.
- Supports processes related to evaluating insurance needs.
Recent Neighborhood Sales Defined
Recent neighborhood sales list properties within a 2-mile radius of subject property sold within the last year. Up to
10 properties can be listed, however, the number will vary based on sales activity.
Confidence Scores Defined
HVE reports provide a Confidence Score in addition to the estimated value of a property. Confidence Scores indicate
the difficulty of estimating a value when the target price is not known in advance.
You will see 3 possible Confidence Scores on an HVE report—high, medium and low. The scores are directly linked to the
amount of data available and the quality of that data.
Freddie Mac has conducted a great deal of research around the accuracy of the traditional appraisal process when the
sale price of the subject property is not known. We leveraged the results of this research and other published data
when we constructed HVE Confidence Scores.
Of all the AVM scoring systems, the HVE Confidence Score is the most reliable and easiest to use because it is tied to
the accuracy of the traditional appraisal process. HVE Confidence Scores start by calculating a standard deviation
based on the difficulty both HVE and a human appraiser would have determining a property's value.
The standard deviation considers the number of comparable properties and how recently they were sold. When analyzing
comparables, HVE evaluates property type, neighborhood uniformity, etc. If a standard deviation is exceedingly high,
indicating the data appears to be inconsistent or the neighborhood property values vary drastically, HVE will not
return a value.
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