How Alternative Data Could Improve Access to Mortgage Credit

One of the most vital steps along the path to owning a home is access to mortgage credit. Researchers examining the racial gap that exists in homeownership and the wealth that accompanies it recently looked into alternative data used in securing credit, and whether it would promote or impede fair lending goals.

The National Association of Realtors (NAR) commissioned a research paper to review three major types of alternative data that could be used to evaluate a consumer’s creditworthiness: credit proxies, banking data, and non-financial personal data.

According to NAR, the use of additional data to determine prospective buyers' creditworthiness will increase opportunities for homeownership among Black and Latino Americans.

The paper, Tipping the SCALE: How Alternative Data in Credit Scoring Promote or Impede Fair Lending Goals, authored by industry thought leaders and PhDs Ann B. Schnare and Vanessa Gail Perry, examines how reforms to current credit bureau data and scoring models, which fail to consider many common household expenditures such as rent and utility payments, would provide a more comprehensive view of a household's credit performance and dramatically increase opportunities for property ownership.

"Minorities are far more likely to be unscorable or have relatively weak credit scores using traditional credit bureau data," Schnare—an erstwhile U.S. Department of Housing and Urban Development advisor and President of her own consulting firm specializing in housing and mortgage finance—said during a virtual event hosted by NAR to discuss the findings. "Incorporating additional data into the credit evaluation process can open doors for many deserving borrowers and boost minority homeownership rates."

Perry added that the rise of "big data" exponentially expands credit-scoring options. However, she added, "predictability is not enough to justify the use of certain kinds of data. Their use must also be consistent with broader social and ethical values."

Their findings, discussed in this video presentation by NAR, outline a solid five-factor framework of considerations that could contribute to fair lending:

• Societal Values: Does it respect social and ethical norms like right to privacy
• Contextual Integrity: Regardless of predictive value, is it relevant to mortgages
• Accuracy: Does the data accurately reflect the household's financial situation
• Legality: Would the use of the data have a disparate impact on protected classes
• Expanded Opportunity: Would the use of the data increase the number of qualified borrowers

They call the model "SCALE" for short.

It adds to the conversation and calls for action, but, say NAR representatives, "Homeownership rates for Black and Latino Americans have lagged those of White Americans for decades, highlighting the need to review existing tools and identify new credit valuation processes."

This highlights the ongoing need to review existing tools and identify new credit valuation processes, according to NAR President Charlie Oppler.

"A borrower's credit report and credit score are the gateway to a mortgage," he said. "But for too long, inaccurate credit reporting methods have raised the cost to borrow while limiting access to mortgage credit for prospective borrowers, particularly those from minority populations and rural communities. NAR is eager to apply this new research to help shape our policy positions and advocacy efforts in the future."