Tokenized deposits could raise US credit costs: Dallas Fed economists

Tokenized deposits could make bank funding less stable and raise credit costs for US households and businesses, according to an analysis by two economists at the Federal Reserve Bank of Dallas. Economists Rosie Levy and Srini Ramaswamy said instant settlement could allow depositors seeking higher yields to switch banks more quickly.

By AI NewsroomPublished about 11 hours agoUpdated about 11 hours ago0 views
Tokenized deposits could raise US credit costs: Dallas Fed economists

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Key Facts

  • Fact 1: The economists estimated that if deposits became 10% more sensitive to interest rates, banks’ capacity to hold long-term loans and other assets could fall by about $700 billion.
  • Fact 2: In a separate scenario, deposits remaining at banks for 10% less time could reduce that capacity by about $580 billion.
  • Fact 3: Both figures are expressed in 10-year equivalents and do not represent direct reductions in lending.
  • Fact 4: Banks develop networks for tokenized deposits On Tuesday, 39 US state banking associations formed the BankChain Alliance to develop a nationwide network supporting tokenized deposits, stablecoins and automated settlement.

Tokenized deposits could make bank funding less stable and raise credit costs for US households and businesses, according to an analysis by two economists at the Federal Reserve Bank of Dallas. Economists Rosie Levy and Srini Ramaswamy said instant settlement could allow depositors seeking higher yields to switch banks more quickly.

They said programmable deposit tokens and agentic artificial intelligence could automate the transfers, shortening the time that deposits remain at individual banks and making them more sensitive to interest rates. The economists estimated that if deposits became 10% more sensitive to interest rates, banks’ capacity to hold long-term loans and other assets could fall by about $700 billion. In a separate scenario, deposits remaining at banks for 10% less time could reduce that capacity by about $580 billion.

(Original synthesis pending human/AI review — generated by the stub provider by selecting real sentences from the source material, not by writing new analysis or commentary.)

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