Forbes Article Rating

Payments For Some Student Loan Borrowers Could Could Triple In 2025

Jan 22, 2025 View Original Article
  • Bias Rating

    22% Somewhat Conservative

  • Reliability

    45% ReliableFair

  • Policy Leaning

    20% Somewhat Conservative

  • Politician Portrayal

    -3% Negative

Bias Score Analysis

The A.I. bias rating includes policy and politician portrayal leanings based on the author’s tone found in the article using machine learning. Bias scores are on a scale of -100% to 100% with higher negative scores being more liberal and higher positive scores being more conservative, and 0% being neutral.

Sentiments

Overall Sentiment

36% Positive

  •   Liberal
  •   Conservative
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Bias Meter

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Bias Meter

Contributing sentiments towards policy:

60% : Republican leaders in Congress are floating the possibility of repealing the SAVE plan in an upcoming reconciliation bill primarily intended to extend expiring tax cuts.
51% : Here's how that could change a their monthly payment:The biggest increases in student loan payments will hit borrowers who will experience a combination of these issues -- borrowers in SAVE who, as a result of an expected congressional repeal or court decision, may have to switch to a different IDR plan and update their income information after not being required to do that for the last several years.
43% : Here's what this might look like:There are limited but potentially useful ways for borrowers to mitigate some of these anticipated increases to student loan payments.
36% : A perfect storm is brewing for millions of federal student loan borrowers, who may experience dramatic increases in their monthly payments later this year.

*Our bias meter rating uses data science including sentiment analysis, machine learning and our proprietary algorithm for determining biases in news articles. Bias scores are on a scale of -100% to 100% with higher negative scores being more liberal and higher positive scores being more conservative, and 0% being neutral. The rating is an independent analysis and is not affiliated nor sponsored by the news source or any other organization.

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