Christy Moss, CMB, of FormFree: It’s Time to Stop Punishing Borrowers with Outdated Underwriting

Christy Moss, CMB, is chief customer officer with FormFree, Athens, Ga. In this role, the 30-year mortgage industry veteran leads voice-of-customer initiatives and oversees sales. Previously, she held positions with Fannie Mae, CitiMortgage, Wachovia and GE Capital Mortgage Services.

The Department of Housing and Urban Development’s recent move to reduce mortgage insurance premiums for Federal Housing Administration borrowers is commendable and also overdue. For too long, the housing finance industry has overestimated the risk profiles of FHA borrowers, who are more likely to be Black, Hispanic and first-time home buyers than the general homebuying population. As a result, the very borrowers who need access to affordable home financing the most have paid dearly because our industry has misjudged their ability to support a mortgage loan.

Setting MIPs too high for the actual risk posed by FHA borrowers is one way our industry’s outdated underwriting practices have punished young families and minorities. The GSEs’ and FHA’s approach to underwriting also penalizes millions of fiscally responsible consumers with a stubborn overreliance on traditional credit scoring models to assess their ability to repay a mortgage loan.

Now, there is nothing inherently wrong with traditional credit scoring models. In fact, they are excellent tools for gaining insight into consumers’ repayment history. However, there is a problem with the way they are treated as the end-all-be-all mortgage underwriting metric. Because traditional credit scoring models are based on a very narrow range of financial behaviors, consumers who don’t rely on revolving or installment accounts have lower credit scores or no credit score at all. And because FHA and the GSEs do not make it easy for lenders to evaluate other indicators of ability to pay, millions of consumers are unfairly characterized as risky loan candidates.

Even more problematic, the industry’s overreliance on traditional credit scoring models perpetuates the same systemic racial bias that it very vocally purports to combat. We know that Black and Hispanic consumers are less likely to use credit cards, and their credit scores suffer for it. The Consumer Financial Protection Bureau has found that Black and Hispanic consumers are nearly twice as likely to be credit invisible or unscorable as white and Asian consumers. Research from the Urban Institute shows that 45% of Black consumers and 31.5% of Hispanic consumers have subprime credit scores, whereas only 18% of white consumers do.

Now, I’ve heard it argued that residual income analysis is subject to the same racial bias as credit scoring because Black and Hispanic consumers are likely to have less savings, earnings and residual income. However, I think this line of thinking misses two very important points.

For one, while it is true that residual income analysis cannot solve for racial wealth inequity, it does enable lenders to extend financing to more consumers of color who would have otherwise been declined. On the other hand, looking at traditional credit scoring models alone entirely boxes out many consumers of color from homeownership who have the ability to pay.

Secondly, traditional credit scoring models favor arbitrary financial behaviors that communities of color are less likely to adopt, whereas residual income analysis evaluates consumers’ underlying ability to make payments. It’s deeply troubling that when two consumers make identical purchases, the consumer paying with cash or debit — the payment methods preferred by people of color — is punished while the consumer who uses a credit card and pays the balance a month later is rewarded. Both consumers are responsibly managing their money and spending within their means, yet they are not treated as such. From the consumer’s perspective, the system seems absurd and rigged, and they are right to think so.

To be clear, I am not advocating for the abolition of credit scores. They help make it possible to evaluate creditworthiness more objectively. But in 2023, when financial transactions are almost exclusively digital and tracked with great detail and precision, we have many tools for underwriting home loans more equitably and inclusively. Thankfully, the industry is beginning to catch on.

Last year, the Federal Housing Finance Agency and the FHA launched initiatives to encourage lenders to use positive rental history as an additional factor in evaluating an applicant’s creditworthiness. This change makes credit evaluation more comprehensive and equitable, especially for first-time homebuyers transitioning from renting.

But there’s still more work to be done.

Other alternate data not typically found in credit reporting, such as cell phone and utility payment histories, can provide a more comprehensive picture of a borrower’s creditworthiness and help lenders make more informed decisions. The Office of the Comptroller of the Currency’s Project REACh initiative has established an Alternative Credit Assessment Workstream to develop alternative credit assessment methods that expand access to mainstream credit in collaboration with financial institutions.

Using cash-flow analysis — which looks at the inflow and outflow of funds through consumers’ bank accounts — to identify alternative data points has been especially promising since more than 96% of American households have either banking or prepaid accounts, and direct-source asset reports make this information operationally feasible to evaluate. Research from FinRegLab further indicates the strong potential for direct-source cash-flow data to improve current underwriting practices.

While cash-flow analysis is able to provide insight into what a consumer earns each month, the amount they spend and how these average out over time, there are other considerations. Simple cash-flow analysis does not necessarily identify and exclude outlier windfalls and shortfalls or account for discretionary spending that a consumer could curb.

Other supplemental underwriting assessments, such as residual income analysis, go beyond what cash-flow analysis is capable of by offering lenders another set of glasses for understanding default risk and ability to pay. Like cash-flow analysis, residual income analysis is calculated from a consumer’s bank and credit card transactions. However, residual income analysis is more refined because it can distinguish between mandatory and discretionary expenses, further sort discretionary expenses into weighted categories and apply behavioral economics to model reasonable reductions in discretionary spending. Additionally, residual income analysis can detect cash-flow anomalies and adaptively limit the impact of outliers on ability-to-pay assessments.

Ultimately, to truly level the playing field and ensure that all borrowers have access to the American dream of homeownership, FHA, the GSEs and lenders will need to embrace smart applications of alternative data that complement other data points such as credit scores.

(Views expressed in this article do not necessarily reflect policies of the Mortgage Bankers Association, nor do they connote an MBA endorsement of a specific company, product or service. MBA NewsLink welcomes your submissions. Inquiries can be sent to Michael Tucker, Editor, at mtucker@mba.org.)