Sanders to introduce bill to end Social Security garnishment for student loan debt
Sen. Bernie Sanders (I-Vt.) announced Monday he will introduce legislation seeking to prevent the federal government from garnishing Social Security benefits for seniors with unpaid student loan payments. The bill, titled the Stop Social Security Garnishment Act of 2026, proposes barring the Education Department from cutting an individual’s Social Security retirement or disability benefits to...
A new proposal from Senator Bernie Sanders aims to protect Social Security recipients and people with disabilities from having their benefits reduced due to unpaid federal student loans. The proposed legislation, named the Stop Social Security Garnishment Act, would prevent the government from garnishing Social Security payments to collect defaulted student loan debt.
The bill, expected to be introduced next month, has received support from Senators Elizabeth Warren and Ed Markey. Senator Sanders argues that the rising costs of healthcare, prescription drugs, groceries, and housing make it unacceptable for seniors to have their Social Security payments garnished to repay student debt. Currently, around 9 million to 9.5 million borrowers are in default on federal student loans, with over 3 million Americans over the age of 62 carrying student loan debt.
Half of Social Security beneficiaries with student loans have reported sacrificing medical care or prescriptions due to garnishment. If passed, the Stop Social Security Garnishment Act would generally amend existing law and prohibit the government from offsetting federal benefits to recover defaulted student loan debt, which currently allows up to 15 percent of a monthly Social Security payment to be garnished to collect these debts.
While some have concerns about the proposal from a fiscal policy perspective, supporters argue that it would provide much-needed relief for affected borrowers, allowing them to receive their full Social Security benefits without reduction.
Written by urgent.news from Newsweek's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
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