Federal Reserve Board requests public comment on a proposal to establish a "payment account," which legally eligible financial institutions could use for the specific purpose of clearing and settling their payments
The Federal Reserve Board is seeking public comment on a proposal to create a new 'payment account' for eligible financial institutions to clear and settle payments, a move aimed at supporting innovation while managing risk [1]. The proposal, which is substantially similar to a prototype outlined in a December 2025 request for information, would grant direct access to Federal Reserve payment services to reduce costs and increase speed [1]. Many institutions seeking such access are not federally insured [1]. Payment account holders would not have access to intraday credit or the discount window, would not earn interest on balances, and would be subject to automated controls to prevent overdrafts [1]. The proposal affirms that Reserve Banks would expect account holders to mitigate illicit finance risks and does not change legal eligibility for access [1]. This initiative reflects a broader trend of regulatory adaptation to technological evolution in financial services. In other sectors, such as digital streaming, novel approaches like the SAGE framework have been developed to manage complex risks, such as fraud detection where legitimate user behavior can mimic coordinated attacks [2]. Similarly, the Fed's proposal employs tailored controls, like balance limits based on expected payment activity, to address specific risks within a new operational framework [1]. The Board is encouraging Reserve Banks to temporarily pause decisions on certain access requests to allow for consistent policy implementation [1]. The public comment period will last for 60 days [1]. The final structure must balance innovation with stability, a challenge paralleled in fields like federated learning, where frameworks are designed to ensure consistent and valid outcomes across multiple independent sites under specific conditions [3].
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Context we found (3)
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arxiv.org —
https://arxiv.org/abs/2605.20157v1 ↗
Music streaming fraud, where bad actors artificially inflate stream counts to manipulate chart rankings and royalty payments, poses a significant threat to streaming services and legitimate content creators. Traditional fraud detection approaches struggle with a critical challeng…
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arxiv.org —
https://arxiv.org/abs/2605.20125v1 ↗
Privacy constraints have driven the rise of federated learning (FL), which enables multi-site analyses without sharing individual participant data. We develop a framework for FL with missing data, identifying conditions under which the complete case (CC) estimator is preferred ov…
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arxiv.org —
https://arxiv.org/abs/2605.20101v1 ↗
This paper demonstrates the computational design of soft elastomeric pneumatic actuators using nonlinear topology optimization. An existing density- and porohyperelasticity-based topology optimization framework was extended from 2D to 3D and used to generate two manufacturable ac…