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Real-world assets (RWAs) are becoming more popular in Web3, but what factors need to be addressed in order to maximize the value of this innovation? Let’s do a deep dive into the nuance of RWA tokenization and explore the ways AI tooling can improve transparency for both asset buyers and DeFi lenders.
Real-world assets (RWAs) may inspire a new age of blockchain adoption, providing an important bridge between traditional finance and decentralized finance. While RWA tokenization has been explored by many developers around the world, questions remain about the real value added by tokenization. More specifically, tokenization in its current form doesn’t present a comprehensive framework for data, making it difficult to provide on-chain proofs of cash flow, valuation and creditworthiness. What factors need to be addressed in order to maximize the benefits of this innovation and usher in a new era of DeFi?
RWA tokenization efforts often focus on the liquid nature of blockchain-based digital assets, developing compliance solutions that ensure that these assets can be sold to and purchased by an approved demographic of investors. Security token standards have programmable features, allowing issuers to whitelist investors, set transfer restrictions and even restore the cap table in the event of an exploit. While these developments are impressive, they only focus on issuance and offering, while due diligence remains a complicated off-chain process. Without a rich data ecosystem on-chain to support RWAs, these tokenized assets may be little more than an additional layer of obscurity for investors.
Better Data = Better Assets
Web3 needs better assets. The blockchain ecosystem deserves a comprehensive treatment for RWAs, going beyond proxy assets to deliver a high-definition view of value and health. Choosing a primitive to start with is especially important. Many RWA developers favor fungible standards, a straightforward path to fractionalization, but this skips an important step: a holistic approach towards minting the asset itself on-chain.
In the case of many RWAs, these assets are non-fungible by nature, but existing non-fungible standards have limited metadata, thus they are not entirely suited for tokenization by default. Oraichain Labs US has spent considerable time exploring this issue, developing a system that leverages Merkle Proofs to create an immutable chain of record keeping that directly leads to the non-fungible asset itself. The ultimate goal is to create a 1:1 replication of the underlying asset, updated in real time with secure data feeds and validated via collective intelligence.
In practice, this means the act of minting a RWA would result in the creation of a Merkle tree. Each piece of data committed would then become a leaf of this tree, directly connected with cryptographic proof to the asset. This system fundamentally improves the storage capacity of on-chain RWAs while providing a clear method for organizing data points, events, documents and revision history.
While this may sound a bit complex, the result is a superior user experience for asset owners, issuers, brokers, investors and even creditors. Rather than simply viewing a token address, parties would have the opportunity to view a more detailed record of the asset. In the case of businesses, for example, this means ownership history, licenses, permits, cash flow, debt, PNL, even governance events can be stored with on-chain proof. Decentralized file storage systems, like Eueno, are also essential to this equation, ensuring data resilience, availability and verifiable timestamps for every transaction.
Collective Intelligence for Validation
Creating a clear method for bringing real-world data on-chain is part of the solution, but in a practical sense, any data submitted needs to be scrutinized and validated. This is Web3, right? As the saying goes, “Don’t Trust, Verify”. The possibility that an asset owner would choose to misrepresent the nature of the underlying asset is a tangible risk that should be approached from all angles.
This begins with KYC. Every asset owner must be verifiable, obligated to only submit documentations and statements that are true. Whenever possible, all material documentations should be reviewed by a pool of specialized validators, professionals equipped with experience and even license to verify the authenticity of key documentations. Collective intelligence can also be used to produce valuations, helping to keep owners and issuers honest when listing an offering. In some cases, this may also mean integrating payment systems and accounting tools to capture cash flow and expense data in real time. Again, considering real world business as an example, why should interested parties be asked to review quarterly or annual reports rather than view cash flow in real-time with on-chain proof?
The tools exist. Use them.
AI for Auditable RWAs
Now we have an abundance of data we can trust, complete with on-chain Trustworthy Proofs and validation. This is where AI can become extremely valuable, especially for investors that lack the manpower and expertise to sort through and interpret documentation. AI-powered analytics and visualization tools can be used to aggregate key figures and provide a user-friendly interface for performance tracking. Large Language Models (LLMs) can be used to quickly ask questions, query and investigate asset health according to the parties interests. Eventually, exploring on-chain RWAs may feel like speaking to the asset itself.
AI-enhanced due diligence can help with both the investigation of individual assets, across multiple assets in the same class, and even between asset classes, aiding investors with portfolio management. To go a step further, AI tools may be especially useful for detecting anomalous transactions, fraudulent documentations, and untrustworthy asset owners, protecting investors from exposure to toxic assets altogether.
Beyond due diligence for investors, these AI tools can also be valuable for potential creditors, helping lenders establish interest rates that appropriately match the risk profile and execute decisions quickly. Ultimately, the stack of solutions and protocols discussed in this paper should lead to better risk management and a more confident DeFi ecosystem.
RWAs + DeFi
The introduction of verifiable cash flow positive assets to the DeFi ecosystem will not only ensure borrowing opportunities for millions of qualified RWA owners, but will enable creditors to explore profitable lending opportunities backed by auditable on-chain documentation and financials. The value of this should not be underestimated.
In the current state of affairs, DeFi is high-risk and the crypto markets are a zero sum game. As a result, leverage is primarily used to make speculative trades in order to repay loans. Can you imagine a world where borrowers are using these capital infusions to scale revenue streams? In this reality, interest paid may equate to ‘new money’ entering the Web3 ecosystem, legitimately earned through real-world economic activity. This is the point where traditional finance and decentralized finance merge.
In conclusion, my confidence in the blockchain ecosystem has never been stronger than it is today. Within the Oraichain ecosystem, we’ve seen a consistent effort to build out the infrastructure necessary to achieve some of the ambitious ideas written in this article. What I’ve described here is not out of reach, in fact, it is just around the corner. Let’s stop talking about the next million crypto holders and start talking about the first million businesses on-chain.
