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Witnesses tell Congress national privacy rules and privacy‑enhancing technologies are core to trustworthy AI in finance
Summary
Experts recommended a U.S. federal data privacy framework, wider use of privacy‑enhancing technologies for model training, and clearer supervisory guidance so financial institutions can train high‑quality models without compromising consumer privacy.
In testimony before the House Financial Services subcommittee, privacy and industry experts recommended a national data privacy framework and greater adoption of privacy‑enhancing technologies (PETs) to support model training and protect consumer financial data.
Why it matters: Panelists said model quality depends on access to rich, permissioned datasets while privacy safeguards are essential to preserve consumer trust and avoid discriminatory outcomes when…
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