Applying for a mortgage is one of the biggest demands most people will make in their lifetime; being refused for a simple omission can delay the process by several weeks. According to a new report from Zillow, the rate at which black applicants were denied mortgages is 84% higher than that of white applicants in 2020 (the latest year for which data is available). This is up from the 74% rate seen in 2019.
According to a new report from Zillow, the rate at which black applicants were denied mortgages is 84% higher than that of white applicants in 2020 (the latest year for which data is available). This is up from the 74% rate seen in 2019.
Nationally, 19.8% of black applicants were refused a mortgage in 2020, the highest rate of any race, and is well above the 10.7% refusal rate for white applicants .
The data for this report was taken from the Residential Mortgage Disclosure Act which requires financial institutions to publicly disclose information about each mortgage loan. This anonymized data should show how well lenders are meeting the needs of their communities, compile raw data that public officials can use in decision-making processes, and most importantly, shed light on discriminatory lending practices.
“Households of color, as well as renters and low-income households, were more likely to report experiencing housing and economic challenges as a result of the pandemic,” wrote Nicole Bachaud, economist and market analyst for Zillow. “Black households were more likely than whites to report job or income loss and difficulty meeting mortgage or rent payments. This disproportionate impact of the pandemic on black households has stalled efforts to close gaps in access to credit, homeownership, home values and mortgage denial rates, making the journey to equity even slower than it already was.
Previous research from Zillow shows that income inequality is the root cause of inequality in mortgage space for people of color. According to the HMDA, black borrowers had an average income of $67,000 in 2020, compared to a median of $83,000 for all applicants.
“This may help explain why black mortgage applicants had smaller down payments in 2020 than applicants of other races,” Bachaud wrote. “Black applicants filed a median of 3.5% on home purchase applications, barely above the absolute minimum of 3% required for most conventional loans, and less than half the down payment. overall median of 8.9% of all applicants.”
Black applicants also applied for cheaper homes in 2020 compared to other races – $225,000 compared to $275,000 for all applicants.
The study found that the most common reason black applicants were turned down was a lack of credit or credit history (37%). Lack of access to traditional financial systems in predominantly black communities as well as a higher prevalence of non-traditional banking services such as payday lenders are two key factors that contribute to poor credit health not only of borrowers, but communities as a whole.
“This lack of credit is leading to increased mortgage denials for credit-related reasons, but even those with otherwise decent credit are being impacted by America’s uneven financial landscape,” Bachaud wrote. “About one in seven black households were unbanked in 2019, and more than half have no savings for retirement. The fact that there are very few (or sometimes no) traditional depository institutions in predominantly black communities is one reason for this.Not having access to bank accounts makes it difficult to save money for lump sums like a down payment, regardless of income.
But better credit and higher savings rates alone aren’t silver bullets that should balance the market in favor of black mortgage seekers, even those who manage to become homeowners. Overcoming the enormous barriers to homeownership is the first step, but far from the last, on the road to housing parity. The value of homes owned by Blacks themselves has long lagged behind those of other races – in October 2021, homes owned by Blacks were worth 16.7% less than the typical American home, which leaves less net worth for black owners to exploit, everything else equal.”
“Part of this issue revolves around disparities in home valuation, including property tax assessments and rates, which often skew against homeowners of color and/or largely non-white neighborhoods,” said concluded Bachaud. Black homes and homes in black neighborhoods are often assessed at lower values, but tax assessments are higher than they should be. This causes black homeowners to receive less than they should in sales and pay more than they should in taxes, further widening the wealth gap”
A silver lining is that black-owned home values are rising faster than other races — 1.5 percentage points ahead of all home values — and are expected to rise steadily in 2022.
Although there is no easy formula to follow, in October the Urban Institute and the Federal Home Loan Bank of San Francisco (FHLBank) committed $1.5 million to a new program called “Racial Equity Accelerator for Home Ownershipwhich will “develop and incubate innovations in housing finance, including underwriting and fintech.”
“The yawning ownership gap between white people and communities of color has only grown and with it, BIPOC [Black, Indigenous, and people-of-color] communities have missed out on opportunities and an accumulation of wealth,” said the president of the Urban Institute Sarah Rosen Wartell. “The evidence is clear and the time has come to seize the moment, and every segment of the mortgage industry should work together to overcome long-standing obstacles.”
San Francisco-based FHLBank will work with its member financial institutions to promote equal home ownership, create economic development projects and expand access to affordable housing. The two-year program and financial contribution reflect the bank’s “call to action” for the industry to assess the “systemic barriers that continue to prevent people of color from homeownership and put implements tangible solutions that enable and guarantee fairness in the purchase of a home. ”
Click here to see the full study, including a breakdown of state-level data.