Veros AVM Unaffected by Historical Redlining Says Study


Veros Real Estate Solutions, a California-based company specializing in enterprise risk management and collateral valuation services, recently conducted research to examine the potential for bias in home valuations generated by its VeroVALUE automated valuation model (AVM) when analyzed across boundaries in historical redlining maps.

The study centered on AVM predictions for single-family properties in redlined versus non-redlined neighborhoods close to one another in Los Angeles. Veros’ economists took this approach because mortgage funds were historically abundant for non-redlined areas yet scarce or non-existent for redlined areas. Single-family homes on both sides of the boundaries were the areas selected for analysis.

Statistical multiple regression analysis was used to investigate which physical home attributes were responsible for the differences seen in the VeroVALUE AVM estimates. Of particular interest was the role of a location variable (whether the residence was in a redlined area or not) as a determinant of housing prices.

“After controlling for the physical attributes of homes, the VeroVALUE AVM returned comparable estimates for properties on either side of the redline,” says Reena Agrawal, Veros’ research economist.

The homes valued lower on average in historically redlined areas are often the result of property characteristics such as smaller living areas and lot sizes, not due to a lingering bias due to historical redlining.

The study was designed to consider whether all valuation solutions are biased because of historical redlining, as some have intimated. AVMs offer a distinct benefit because they do not rely on any data related to historical redlining maps or demographic information concerning the parties involved in real estate transactions. However, there is the suggestion that any property valuation offering may be unwittingly influenced or biased through the injection of historically biased data rooted in decades-old discrimination.

Map: United States Federal Government, Public domain, via Wikimedia Commons.

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