Differentiating Data Sets Support Financially Inclusive Lending in the Mortgage Industry

This piece originally appeared in the September 2023 edition of MortgagePoint magazine.

A critical first step to establishing wealth for many Americans is the purchase of a home. Research has consistently shown that communities with a high rate of homeownership tend to flourish and be more economically resilient, with children and families more likely to thrive and build generational wealth. However, the reality is that securing a traditional mortgage continues to be a challenge for millions of “credit invisible” consumers.

Although a traditional credit report is still a strong indication of credit history and past financial reliability, a credit report alone doesn’t always provide the full picture of a consumer’s financial profile. Borrowers with thin or unscorable credit files can be locked out of qualifying for a loan, or left to a manual-paper-based process because the entirety of their financial profile is not being considered.

Expanding access to credit and supporting financially inclusive lending are initiatives the entire mortgage industry continues to focus on. Working together, the industry is helping to facilitate greater inclusion in the mortgage lending process by introducing more tools, technology advancements, and access to data to provide visibility to millions of consumers.

The Benefits of Differentiated Data Sets
Differentiated data sets, such as telecommunications (telco), pay TV and utilities insights, offer a solution to barriers in the path of homeownership, benefiting both lenders and borrowers.

Leveraging differentiated data insights alongside traditional credit reports can provide greater visibility into a borrower’s financial profile, helping to create greater homeownership opportunities for millions of consumers.

According to Equifax research, approximately 191 million American consumers—80% of whom have traditional credit histories—could benefit from additional insights into their financial profile. Most U.S. adults have at least one utility bill or cellphone in their name, making utility data a widespread and powerful indicator of past financial reliability.

Anonymized Equifax research delved further into the potential benefits of differentiated data sets, and found that among 225 million U.S. consumers, approximately 30% had the potential to increase their credit score if data like telco, pay TV, and utilities attributes were considered.

The research also noted that the addition of these differentiated data sets resulted in an average increase of around 30 points for millions of subprime consumers, moving them into the near-prime credit scoring band. With the addition of differentiated data sets, consumers can gain more credit access, and obtain more favorable rates.

The Correlation Between Utility Payments and Future Mortgage Payment Performance
A recent study from Andrew Davidson & Company’s analyzed U.S. mortgages from January 2019 for consumers with non-traditional credit histories, young, thin, or no-hit consumers. The study uncovered a strong correlation between positive consumer utility payment history and future positive mortgage payment performance. The correlation becomes more pronounced when borrowers have multiple utility attributes.

This correlation exists across a wide range of credit scores, and is seen prevalently among borrowers in the 600-700 range. Traditionally, this interval of borrowers has been more likely to run into obstacles while trying to obtain a mortgage or may have been offered higher rates based solely on their credit files.

Augmenting credit reports with these differentiated data insights could allow consumers to gain more access to credit while obtaining favorable rates for a mortgage loan rather than being overcharged or receiving prohibitive rates.

Differentiated Data Helps Automate and Streamline the Underwriting Process
In addition to supporting financial inclusion in the mortgage industry, differentiated data alongside a credit report can also streamline the mortgage underwriting process.

It is no secret that manual underwriting—obtaining physical documentation from third parties to determine the credit history of consumers applying for a mortgage loan—is a time-consuming and cumbersome process.

Due to the lengthy nature of this manual process, consumers risk becoming less competitive compared to borrowers with a faster underwriting process. By automating the delivery of verified information, differentiated data can help reduce friction in the manual process, improve efficiency, while also protecting the lender from risk.

A single financial opportunity can be a critical step to establishing individual financial health and generational wealth, changing the trajectory of families and communities for generations. More data drives better decisions.

The addition of differentiated data supports financial inclusion initiatives with the goal of expanding the availability of credit to a wider range of borrowers, creating a clearer pathway to homeownership and greater financial inclusion.