Quantum Security, Quantum Finance

Treasury launches task force to prepare finance for quantum threats

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August 26, 2026 by Ivy Delaney

The U.S. Department of the Treasury has launched the Quantum-Readiness Task Force, following President Donald J. Trump’s Executive Order 14412 to bolster cryptographic protections. This public-private initiative will focus on three workstreams, Sector Alignment & PQC Transition, Third-Party & Vendor Readiness, and Digital Assets and Emerging Technology Risk, to prepare the financial sector for potential cybersecurity challenges posed by advances in quantum computing.

“America must lead in securing the technologies that power our economy,” said Secretary of the Treasury Scott Bessent, as the Task Force builds upon the G7 Cyber Expert Group roadmap for transitioning to post-quantum cryptography.

Executive Order 14412 Drives Quantum-Readiness Task Force Launch

U.S. Assistant Secretary for Financial Institutions Luke Pettit explained that the group will focus on practical, risk-based approaches, including identifying critical dependencies within the financial ecosystem. This coordinated preparation is essential because future quantum computing capabilities threaten to compromise the cryptographic tools currently safeguarding financial data and infrastructure, reinforcing national economic security by ensuring a resilient and orderly transition to post-quantum cryptography, a process that requires both government and industry alignment.

Quantum computing holds significant promise, but it also presents a serious long-term challenge to the cryptographic tools that underpin the U.S. financial system.

Luke Pettit, Treasury Assistant Secretary for Financial Institutions
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Cryptography Quantum Computing
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Ivy Delaney

Ivy Delaney has been working with neural networks and machine learning since the mid-nineties, back when a couple of hidden layers and a long afternoon of training counted as ambitious. She has watched the field go from academic curiosity to the thing quietly running underneath everything, and she brings that long view to quantum computing. For Quantum Zeitgeist she covers the ground where the two fields meet. That means quantum machine learning and the variational algorithms it leans on, and it also means the less glamorous but more interesting story of classical machine learning already doing real work inside quantum machines, decoding error-correcting codes, calibrating noisy hardware and learning the error models that simulators depend on. She writes about the hardware those algorithms have to run on too, and about the post-quantum cryptography scramble that the same hardware has set off. Her stories typically start with the paper, whether that is peer-reviewed work, conference proceedings or an arXiv preprint, with the source linked so you can hold a claim up against the research it came from. She is unimpressed by benchmarks that will not say what they beat, and by demonstrations that only work in the press release.

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