On the evening of July 18, the School of Economics at Fudan University hosted an international financial policy roundtable titled "The Business Opportunities of Stablecoins: Voices from the Industry." During the meeting, Cui Jianjun, Chairman of Shanghai Te-Gao Information Technology Co., Ltd., raised a question: Why do companies like JD.com have a strong desire to issue stablecoins? What is the profit model for the issuing institutions of stablecoins?
Cui Jianjun believes that the commonly perceived "interest rate differential from reserve assets" is merely the tip of the iceberg. For enterprises, the core value of issuing stablecoins lies in building a data and value closed loop independent of the traditional banking system. This allows companies to directly capture the most authentic and complete user behavior data and financial profiles. In the age of artificial intelligence, these high-dimensional real-time data are the "golden fuel" for training and optimizing commercial models, with strategic value far exceeding short-term interest margin gains.
Based on his years of practical experience in blockchain technology, Cui Jianjun believes that in the long run, stablecoins and RWA will bring significant changes to the global monetary and financial systems, and this change is as important as the development of artificial intelligence. Although there are many challenges in the short term, such as regulatory issues. "Although the road is long, there are opportunities," said Cui Jianjun.
Cui Jianjun emphasized that for the healthy development of the stablecoin market, two key issues must be addressed: first, stablecoins should not be limited to driving the market through buying and selling transactions, which is neither sustainable nor encouraged by national policies. Instead, they should return to their role of supporting real-world value. The vitality of stablecoins ultimately must come from their anchoring to RWA. When real-world assets are tokenized, they need a stable and efficient on-chain trading medium. RWA creates continuous real application scenarios and rigid demand for stablecoins; secondly, promote the circulation and activity of the stablecoin market through decentralized financial markets (DeFi) and other methods. For example, credit creation between stablecoins.
Regarding practice, Cui Jianjun also stated that in the past, the core issue of asset on-chain was the "last mile" data credibility problem: he pointed out that after assets are on-chain, blockchain can ensure data immutability, but how to ensure the authenticity of the source data before it is on-chain has always been an industry challenge. "By leveraging IoT technology, we have effectively solved this problem," said Cui Jianjun, sharing his company's solution. "We can now not only achieve automated and unmanned on-chain data, but also ensure that data cannot be tampered with from the moment of collection at the physical level."
The following is the full transcript of Cui Jianjun's speech (approved by the speaker):
First of all, thank you, Professor Yang, for the invitation. I have been engaged in blockchain technology for many years and have some understanding of these technologies and applications. However, I have never had the time to systematically organize this knowledge. A few weeks ago, I had the opportunity to spend several days deeply understanding this field, and today I hope to share these thoughts with you.
In the past, when discussing blockchain technology, especially with government-related projects, the concept of "decentralization" often faced misunderstandings. Eventually, a colleague suggested that I stop mentioning "decentralization," so I proposed the concept of "multi-centerization." How multi-centered should it be? The minimum number of consensus nodes listened to this and were willing to support this direction.
Now, I will first present my conclusion. My views are similar to those of Professor Wang Shanshang. From a medium- to long-term perspective, stablecoins and RWA will bring great changes to the global monetary and financial system. The impact of this change may be as profound as that of AI. Because if we classify AI as productivity, then blockchain belongs to production relations.
These two will advance together like "two legs." However, in the short term, challenges still exist, especially in regulation. We may still be in the "multi-centerization" stage, where the traditional centralized system and decentralized technology will coexist and interweave. This progress may be relatively slow. If regulators fail to understand these technologies, they may delay action. Although the road is long, there are still opportunities.
Regarding the issue of making stablecoins large, I believe that stablecoins should not just circulate in place, nor should they rely solely on buying coins to drive the market. Although this approach is feasible, it is not a long-term solution, nor is it a direction encouraged by the state. Ultimately, the value of stablecoins will come from the support of RWA, because these assets will bring actual demand and form a stable market demand.
Secondly, stablecoins need to circulate, and the market needs to remain active. For example, the DeFi market (Decentralized Finance, abbreviated as DEFI) will play an important role in this process. Even if using stablecoins as collateral may not be allowed, our innovation will quickly solve these issues. Including credit creation, which is possible. For example, USDC can create credit for USDT, and this method is feasible.
Next, I would like to share some practical considerations. Why do companies like JD.com have a strong desire to issue stablecoins? Besides the interest rate differential from currency storage, the most important reason is the ability to bypass traditional banks and directly obtain customer behavior data and user profiles. Currently, JD.com cannot directly obtain data from banks, but if it can obtain data through stablecoins, it will be particularly beneficial for its own scenario development using AI technology.
I also want to briefly introduce some of the projects we are currently working on or participating in. The content discussed today is mostly technical, which may be a bit difficult to understand.
As mentioned earlier, RWA refers to real-world assets. Assets need to be on-chain, and the security and status of assets are always the top priority.
Previously, the core pain point of on-chain was the "last mile" problem. After on-chain, the authenticity of the data is not an issue, but ensuring its authenticity before on-chain has been a long-standing problem. By leveraging IoT technology, we have effectively solved this problem. Now, we can effectively achieve automated on-chain and ensure that data cannot be tampered with manually.
In practice, we have adopted three key technologies:
Internet of Things (IoT) technology: As the "nerve endings" of data, it ensures the authenticity and reliability of information from the source in the physical world.
Blockchain technology: Using consortium chains to build a trusted collaboration network, ensuring traceability and consistency of data during multi-party exchanges.
Artificial Intelligence (AI) technology: After collecting data, use AI models for real-time risk monitoring, status assessment, and accurate pricing.
These three technologies form a "trust loop" from the physical world to the digital world, providing a solid foundation for the full lifecycle management of RWA, especially dynamic risk control and value assessment. We have also collaborated with Fudan University to develop patented technologies, integrating identity information directly into the smallest IoT devices, achieving data collection with rights confirmation.
Based on this framework, we have developed two main platforms.
Zhi Xin Data Platform: It is a next-generation RWA full lifecycle management and service engine, providing core infrastructure for asset valuation, compliant tokenization, post-investment management, and liquidation. It realizes real-time trustworthy on-chain of asset operation data and automatic penetration distribution of equity returns, building a transparent, efficient, and trustworthy value transfer network for RWA assets.
Zhi Xin IoT Platform: It is the core value trust anchor engine for physical world RWA. Used for IoT data collection, ensuring that data is verified from the very beginning.
In addition, we have participated in several specific industry projects, including:
Shangzheng Chain: Launched in October 2020 by the Shanghai Stock Exchange in cooperation with the China Securities Regulatory Commission and Fudan University, it is the first infrastructure project in the securities industry - a trusted data infrastructure. It realizes self-controlled and secure operations, with all used encryption standards being domestic standards (such as SM2, SM3), ensuring compliance with local regulations. So far, Shangzheng Chain provides some core data for evidence preservation, business compliance, regulation, business process optimization, data privacy protection, cross-border financial data, and multi-party data sharing. More than half of the securities companies are now using it.
This is the consortium chain of the entire securities industry. On this platform, there are a large number of operating institutions in the securities industry, especially for the issuance of bonds and stocks, and it will have certain advantages in future communication with the Hong Kong market. Based on this, using data cross-border, for assets and asset status, combined with large models, real-time monitoring can be achieved.
Fenjiu Old Wine Traceability Trading Platform: In terms of asset tracking and data exchange, we have also explored in the wine industry. Through blockchain technology, we have established a full-process traceability and supply chain finance platform from production to sales. This system has been recognized by banks and has begun implementation, providing about 40 billion yuan in supply chain finance support for the wine industry. Centralized systems can manage inventory, but the authenticity of bank-issued bills and their comparison with other alliance data still remains a problem. Through the private key and public key mechanism of the consortium chain, everyone can confirm the authenticity and ownership of the data. This method better guarantees the credibility and security of the data.
The recently highly anticipated Trusted Data Space actually provides real and reliable data support for blockchain, including chain-source and chain-head data and data required by oracles. This system is mainly used to realize the support for data assets, especially patent evaluation, covering comprehensive evaluation of the application direction of patents. AI technology is used for evaluation, and the evaluation results can be provided to banks as valuation references. In recent years, this approach has been favored by banks.
Intellectual Property Value Evaluation Large Model: To address the difficulty in evaluating intangible assets such as patents, we have developed the "Intellectual Property Value Evaluation Large Model" in collaboration with Fudan University, using AI Agent to conduct explainable, multi-dimensional evaluations of IP value, providing credit basis for banks. We are currently exploring a new model for intellectual property RWA issuance.
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