Feb 23 -- The Consumer Financial Protection Bureau (CFPB) today outlined options to ensure that computer models used to help determine home valuations are accurate and fair. The options will now be reviewed to determine their potential impact on small businesses.
“It is tempting to think that machines crunching numbers can take bias out of the equation, but they can’t,” said CFPB Director Rohit Chopra. “This initiative is one of many steps we are taking to ensure that in-person and algorithmic appraisals are fairer and more accurate.”
When underwriting a mortgage, lenders typically require an appraisal, which is an estimate of the value of the home. While traditional appraisals are conducted in-person, many lenders also employ algorithmic computer models. These models use massive amounts of data drawn from many sources to value homes. The technical term for these models is automated valuation models. Both in-person and algorithmic appraisals appear to be susceptible to bias and inaccuracy, absent appropriate safeguards.
Obtaining an accurate estimate of a home’s worth is one of the most important steps in the mortgage process for homebuyers. Inaccurate valuations, both too high and too low, can pose risks to consumers. Given their crucial role, the Dodd-Frank Wall Street Reform and Consumer Protection Act tasked the CFPB and other regulators with implementing rules on these models.
Overvaluing homes can put family wealth at-risk, create reselling challenges, and lead to higher rates of foreclosure. Homes can be overvalued for numerous reasons. For example, during the run-up to the 2008 collapse of the housing bubble, housing prices became inflated for reasons that included lenders extending mortgage credit—often with toxic or predatory terms—without regard to borrowers’ ability to repay. In other situations, supply can become constricted and unable to keep pace with demand.
Low valuations can jeopardize home sales and prevent homeowners from refinancing, which makes it harder to build wealth or make repairs. Systematically low valuations driven by biased appraisers may exacerbate existing disparities in the housing market. The Federal Housing Finance Agency recently identified discriminatory statements in some home appraisals, and both Fannie Mae and Freddie Mac have found appraisal disparities for communities and borrowers of color. Homeowners and homebuyers are often dependent on appraisers’ views of a community and of the people that live within it. When those views are negative, the undervaluing of homes can be the result.
Computer models and algorithms are additional tools for mortgage lenders and appraisers to improve valuation accuracy. However, automated valuation models can pose fair lending risks to homebuyers and homeowners. The CFPB is particularly concerned that without proper safeguards, flawed versions of these models could digitally redline certain neighborhoods and further embed and perpetuate historical lending, wealth, and home value disparities.
The CFPB’s options will strengthen oversight of these models. Specifically, the CFPB, along with its federal partners, intends to:
Ensure a high level of confidence in the estimates produced by automated valuation models;
Protect against the manipulation of data;
Seek to avoid conflicts of interest;
Require random sample testing and reviews; and
Account for any other such factor that the agencies determine to be appropriate.
CFPB press release: https://www.consumerfinance.gov/about-us/newsroom/cfpb-outlines-options-to-prevent-algorithmic-bias-in-home-valuations/
CFPB’s Outline, Small Business Advisory Review Panel for Automated Valuation Model (AVM) Rulemaking (42 pages): https://www.consumerfinance.gov/documents/10430/cfpb_avm_outline-of-proposals_2022-02.pdf