Congress quietly centralizes all federal loan data—and adds a hidden fee
H.R. 7789 — Federal Loan Systems Modernization Act of 2026 · Filed by Brad Finstad (R-MN) · 1 cosponsor · Introduced Mar 4, 2026 · Referred to committee
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What it does
This bill creates a single, centralized online platform called Lending.gov to manage federal loan applications and servicing across all government agencies, replacing dozens of outdated, fragmented systems. The General Services Administration will oversee the platform, which will use commercial software and may charge a small fee (up to 0.25% of loan value) to cover operating costs. Agencies must migrate their loan systems to the platform within 3 years, unless the Director grants an exception.
Why we flagged it
This bill establishes a centralized federal loan platform (Lending.gov) using commercial software to consolidate fragmented loan management systems across agencies. It is fundamentally a government IT infrastructure and shared services initiative, not a substantive policy change to lending programs themselves.
What the text implies
- The 0.25% remittance fee on all federal loans serviced through the platform creates a new revenue stream that could eventually exceed tens of millions annually, depending on total federal loan portfolio volume. This fee structure may incentivize agencies to migrate loans to the platform even when cost-benefit is unclear.
- Designation of a 'lead agency' as initial Provider and potential expansion to up to 3 additional shared service providers creates a quasi-privatized loan servicing ecosystem within government. Private vendors operating the platform gain access to detailed borrower data, application patterns, and credit risk profiles across all federal lending programs.
The full analysis lists 5 implications of this text.
Who stands to gain
Commercial software vendors specializing in loan origination and servicing systems; Financial services technology firms (fintech platforms, data analytics providers); Insurance and risk management companies (fraud detection, portfolio analytics)