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Independent Audit Flags ‘Material Weakness’ in ED’s Most Recent Budget Estimates for Student Loan Cancellation

Independent Audit Flags ‘Material Weakness’ in ED’s Most Recent Budget Estimates for Student Loan Cancellation


Hugh T. Ferguson
January 27, 2023
President Joe Biden’s student loan debt relief plan has come under increased scrutiny from an annual audit of the Department of Education’s (ED) finances.
The audit, conducted by KPMG, an independent certified public accounting firm contracted by ED’s Office of Inspector General, reviewed the department’s financial report for fiscal year 2022, and expressed concern over estimates related to costs associated with the debt cancellation plan.
The audit went so far as to decline to render an opinion of ED’s fiscal year 2022 financial statements because it “has not been able to obtain sufficient appropriate audit evidence to provide a basis for an audit opinion.”
KPMG explained that its lack of opinion stemmed from uncertainty surrounding ED’s broad-based debt relief estimates.
“Management was unable to provide adequate evidential matter to support certain key assumptions used to estimate the subsidy costs,” KPMG wrote.
As a part of budget estimates, the department concluded that the program would cost $305 billion over the course of a decade, while another analysis by the Congressional Budget Office (CBO) found that the program would cost $400 billion.
KPMG’s audit found ED’s process for developing its estimate for the program’s take-up rates was not properly designed, where the department’s estimate assumes that the vast majority of eligible borrowers — 81% — would participate in the program.
“Management’s internal controls were not properly designed at an appropriate level of precision to address the relevance and reliability of the underlying data used to develop the take-up rate assumption used in the various loan program estimates,” KPMG wrote, finding “material weakness” in the estimates. “In addition, management did not design sufficiently precise controls over the relevance and reliability of certain data used in other key assumptions for the  Student Loan Model (SLM) cash flow model to develop the subsidy cost estimates.”
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