Artificial Intelligence

AI reveals racial disparities in NYC homeownership

1st December 2020
Lanna Deamer

An analysis powered by Artificial Intelligence (AI) has revealed racial disparities in homeownership, home loans and foreclosures in NYC. The analysis showed that neighbourhoods with a higher proportion of Black and Hispanic homeowners have lower home values even when home age and square footage are the same. 

Additionally, the findings revealed that the total cost of acquiring home purchase loans is higher for Black and Hispanic borrowers than for other races, even when controlling for differences in down payment and home value.

The analysis was made possible through a collaboration between analytics powerhouse SAS and the Center for NYC Neighborhoods, one of the largest non-profits committed to protecting affordable homeownership for low- and moderate-income families.

The work is central to the Black Homeownership Project, an initiative from the Center for NYC Neighborhoods, which is helping advocate for policies that break down these barriers and close the racial wealth gap. In the decade that followed the 2008 financial crisis, Black homeownership in New York City dropped considerably: there were at least 20,000 fewer Black homeowner households in 2017 than there were in 2005. With the devasting economic impacts of the COVID-19 pandemic, compounded by historic barriers to Black homeownership, this rate could drop even more.

To help the Center accelerate its exploration of racial disparities, the Citi Foundation, through its Community Progress Makers programme, helped connect the Center and SAS. From there, a team comprised of data scientists and analytic volunteers - including many members from SAS’ Black Initiatives Group (BIG), one of several employee diversity and inclusion groups at the company - joined forces with the Center to analyse NYC housing data.

For members of the project team, personal experiences made this project even more meaningful. “I’ve seen some of this first-hand,” explained SAS Project Manager Sheri Grice. “Growing up, I saw for myself I was not going to be a homeowner in New York. It was not attainable. From just seeing my peers and my peers’ parents and what they went through, I knew the only option for me was to leave.”

To further explore disparities in homeownership, the Center will be able to use SAS models and visual analytics dashboards to develop and implement targeted programmes to help increase Black homeownership and address key challenges Black homeowners face, including more foreclosures, more tax liens and higher unemployment rates than their non-Black counterparts. This project is occurring at a critical time, as the COVID-19 pandemic continues to disproportionally affect Black communities and as anti-racist protests gain international attention.

“Our collaboration with SAS demonstrates the power of analytics to unearth trends that can be used to empower Black communities at a time of urgent discourse around systemic racism,” Christie Peale, CEO/Executive Director of the Center for NYC Neighborhoods. “The findings will be used by our Black Homeownership Project to design new programmes and to advocate for policy changes that can help to close the racial wealth gap.”

Financial institutions play a critical role in closing the racial wealth gap, and these findings could support their efforts to implement more data-driven policies. Through partnerships with non-profits and other organisations, financial institutions can provide key lending decision data to identify similarities and disparities among various groups. And by applying advanced analytic technology to these important datasets, organisations like the Center can more quickly identify inequalities and take action to protect these communities.

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