Black and Hispanic students were more likely to be subjected to for financial aid audits by the U.S. Department of Education (USDOE) over the last decade, according to an analysis by The Washington Post .
After students turn in their Free Application for Federal Student Aid (FAFSA) the department selects some for verification, asking them to further prove that the information on their application is accurate. The process, meant to reduce fraud and
ensure the integrity of taxpayer dollars, can be time-consuming and is mostly assigned to poorer students.
In the 2019-20 academic year, the department received FAFSA forms from 18 million applicants. Roughly one-quarter were selected for verification.
Somewhere between 11 and 25 percent of students selected for an audit drop out of the process, a phenomenon known as “verification melt.”
USDOE will not share the methodology behind selection, though it has said it uses machine learning to select applicants with the highest probability of errors.
Students in Black and Latino neighborhoods are selected disproportionally. The Post analysis found that students in Black-majority ZIP codes made up only 4 percent of the total number of students selected for verification. However, they were selected at 1.8 times the rate of students from white-majority ZIP codes. Students from majority-Hispanic ZIP codes are selected at 1.4 times the rate as those from white communities.
Some data have suggested that high audit rates are inefficient. The majority of audited students see no change in the value of their award, and only about 3 percent lose eligibility after an audit.
The department has said it is broadly working to decrease the number of people audited.
In the 2019-20 academic year, the department received FAFSA forms from 18 million applicants. Roughly one-quarter were selected for verification.
Somewhere between 11 and 25 percent of students selected for an audit drop out of the process, a phenomenon known as “verification melt.”
USDOE will not share the methodology behind selection, though it has said it uses machine learning to select applicants with the highest probability of errors.
Students in Black and Latino neighborhoods are selected disproportionally. The Post analysis found that students in Black-majority ZIP codes made up only 4 percent of the total number of students selected for verification. However, they were selected at 1.8 times the rate of students from white-majority ZIP codes. Students from majority-Hispanic ZIP codes are selected at 1.4 times the rate as those from white communities.
Some data have suggested that high audit rates are inefficient. The majority of audited students see no change in the value of their award, and only about 3 percent lose eligibility after an audit.
The department has said it is broadly working to decrease the number of people audited.