Articles / tokenization-rwa / Xiao Feng's Hong Kong Speech: Empowered by Privacy Computing, All Commercial Institutions Will Become "Token Factories"
Xiao Feng's Hong Kong Speech: Empowered by Privacy Computing, All Commercial Institutions Will Become "Token Factories"
May 11, 2026 · Source: wublock.substack.com · Topic:
tokenization-rwa · mica-regulation · payments-fintech-infra
Transactions Per Second
1,000 TPS
Expected performance of Fully Homomorphic Encryption (FHE) by the second half of the year.
Token Model Components
3
The Three-Token Model includes equity tokens, utility tokens, and NFTs, fully implemented within HashKey Group.
⦿ Executive Snapshot
- What: Xiao Feng discusses the transformative potential of Privacy Computing and the Three-Token Model in commercial institutions.
- Who: Xiao Feng, Chairman of Wanxiang Blockchain and HashKey Group.
- Why it matters: The speech outlines how integrating AI, blockchain, and privacy computing could revolutionize tokenomics and enable new business models, potentially reshaping the financial landscape.
⦿ Key Developments
- The Three-Token Model, comprising equity tokens, utility tokens, and NFTs, has been fully implemented within HashKey Group, serving as a foundation for future developments.
- Privacy computing advancements, particularly Fully Homomorphic Encryption (FHE), are expected to achieve 1,000 transactions per second (TPS) by the second half of the year, enhancing compliance with regulatory standards.
- The tokenization of data allows commercial institutions to operate as "Token Factories," breaking geographical barriers and enabling real-time micropayments.
⦿ Strategic Context
- The evolution from public chains to consortium chains reflects the ongoing challenges in privacy and compliance faced by traditional financial institutions using blockchain technology.
- The convergence of AI, blockchain, and privacy computing is positioned as a solution to the limitations of current tokenomics and blockchain applications, suggesting a significant shift in business models.
⦿ Strategic Implications
- Immediate consequences include the potential disruption of existing business models in finance and healthcare through the adoption of innovative tokenization and privacy solutions.
- Long-term implications may involve the establishment of a new financial system driven by programmable money and capital markets tailored for AI and machine operations.
⦿ Risks & Constraints
- Regulatory concerns regarding privacy and data protection could pose significant challenges to the widespread adoption of blockchain and privacy computing technologies.
- The competitive landscape may intensify as more institutions adopt blockchain solutions, necessitating robust infrastructure and partnerships to succeed.
⦿ Watchlist / Forward Signals
- The expected launch of FHE chips in the second half of the year could signal a major milestone in privacy computing capabilities.
- Future developments in cross-border payment solutions and consortium chain applications will indicate the success of these innovations in real-world scenarios.
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