Asset tokenization expected to speed capital flows, says Chainlink's Nazarov

Chainlink co-founder Sergey Nazarov predicts asset tokenization will significantly increase capital flow across traditional markets, boosting velocity in asset classes like treasuries, equities, private credit, commercial debt, and real estate. This prediction, shared at Consensus 2025, highlights the need for both high-quality on-chain assets and frictionless payment systems accessible to established institutions.

This assertion is underscored by Chainlink’s new partnership with Kinexys (a JP Morgan blockchain network for institutional tokenized assets) and Ondo Finance. The collaboration focuses on developing payment rails for institutional on-chain trading of tokenized real-world assets. A successful test involved exchanging Ondo’s US Government Treasuries Fund (OUSG) with Kinexys, utilizing Chainlink’s Runtime Environment – a framework bridging legacy financial systems with blockchains. This initiative aims to create a positive feedback loop, driving broader industry success by increasing both on-chain assets and payment systems.

Chainlink’s decentralized oracle network connects smart contracts to real-world data and off-chain systems. Nazarov emphasized the company’s role in coordinating transactions between financial institutions, asset issuers, and regulators. Their “Runtime Environment” is positioned as an upgrade to legacy systems, including COBOL and Java-based architectures, streamlining integration with blockchain technology.

The partnership reflects growing institutional acceptance of cryptocurrencies and Web3, fueled by positive post-2024 US regulatory shifts following Gary Gensler’s departure from the SEC. Nazarov previously advocated for a competitive US advantage in tokenized assets to maintain the attractiveness of US capital markets in a global, permissionless finance landscape. The successful integration of tokenized assets promises to revolutionize capital markets, increasing efficiency and access for a wider range of participants.