US bank Citizens said blockchain technology could accelerate global GDP by removing “frictional taxes” in payments, settlements, record-keeping and ownership verification.
“We believe blockchain adoption can support economic expansion through faster velocity and recirculation of capital, a larger and more innovative investment universe, and an infrastructure better suited to the demands of an increasingly digital and AI-enabled world,” analysts led by Devin Ryan said in a note on Tuesday.
Analysts at the bank pointed to a wave of large institutions deploying on-chain infrastructure into production. They highlighted the New York Stock Exchange’s plans to launch a tokenized securities platform that will support 24/7 trading in U.S. stocks and exchange-traded funds (ETFs) with near-instant settlement, pending regulatory approval.
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Analysts said the move shows existing market operators are integrating blockchain into their core systems to seize new opportunities and avoid disruption.
The economic impact of blockchain will first be manifested through faster capital velocity, the report argues. Round-the-clock markets and near-T+0 settlements reduce trapped collateral and counterparty risk, freeing up balance sheets and allowing the same pool of capital to support more real economic activity.
Analysts said tokenization could expand the investment universe by making it more economical to issue, trade and raise assets that are currently illiquid or complex to operate. This includes not only traditional securities, but also new asset classes tied to the digital economy and on-chain collateral for more efficient lending.
Tokenization is the process of converting real-world assets into blockchain-based tokens.
Blockchain technology works hand in hand with an increasingly digital, AI-driven economy.
As automation drives the growth of machine-initiated transactions, the bank argued that always-on, programmable blockchain rails are best suited to support the growing demand for real-time payments, authentication, and auditability at scale.
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