A bill from US Representative Bill Foster would require the Federal Reserve and other regulators to develop and test public software for spotting financial stress and responding to threats including those linked to AI. The proposal also aims to give smaller financial institutions standard reporting tools, rather than leaving them to navigate a patchwork of manual compliance work.
Watch Desk analysis
What happened
Roll Call reports that Foster introduced the draft bill on Thursday. It would require the Fed to work with other regulators to develop, test and publicly release model software for assessing market conditions in real time, as well as activities including stress testing, fraud screening and monitoring AI risks.
The proposed software would be open source and tested for reliability and accuracy using synthetic or legally permitted historical data, not actual customer accounts. Regulators would take no financial or supervisory action during the study, and would not be required to adopt the resulting software. The bill would set deadlines of one year after enactment for publishing the models and two years for a report to Congress. It is a proposal, not a new system already in use.
Why it matters
The bill puts a concrete idea behind calls for regulators to keep pace with AI-related financial risks: develop shared tools, test them publicly and make the results available. Standard formats and reporting tools could also reduce some of the manual compliance burden for smaller institutions.
There is a useful distinction here between building software to help regulators spot risks and handing software the power to make decisions. Under the proposal, regulators would not take financial or supervisory action during the study, and adoption would not be mandatory. The data rules matter too: the bill calls for synthetic or legally permitted historical data, not live customer accounts.
Our read
The interesting part is the combination of open-source tools, testing and a clear limit on what the study can do. That is more specific than a general promise to “use AI” in oversight, though the bill still has to become law before any of its deadlines or safeguards apply. Public software is only useful if it proves reliable, and “open source” is a starting point for scrutiny, not a magic stamp of accuracy.
What to watch
- Whether the proposal advances through Congress or changes during debate.
- How regulators would test reliability and accuracy, and who could examine the results.
- Whether the proposed standard tools would meaningfully reduce smaller institutions’ reporting workload.
- Whether the bill’s limits on data use and regulatory action remain in the final text.
Discussion spark: Should regulators be required to publish shared, open-source tools for monitoring AI-related financial risks, or could that create more confidence in software than the evidence deserves?
Sources and evidence
- Source update (6 November 2026, 06:13 UTC)
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