The tokenization of real-world assets (RWAs) is emerging as a revolutionary use case for the crypto industry. According to a March 2023 report by investment bank Citi, the market for RWAs is projected to soar to $4 trillion to $5 trillion by 2030. While this transformative potential is clear, the technology has yet to achieve mass adoption. Industry experts believe that artificial intelligence (AI) could be the catalyst to drive tokenized RWA use cases forward.

The Evolution of Tokenized RWAs

RWA tokenization has been a concept since 2018, initially gaining attention with security token offerings (STOs). Unlike the largely unregulated STOs of the past, today’s tokenized RWAs have gained legitimacy and tangibility. Dave Hendricks, CEO and Co-founder of Vertalo, explained, “If a custodian can’t legally hold the asset, and if it’s not considered a high-quality liquid asset by banks, then it might not be seen as a true RWA.”

Vertalo has been at the forefront of tokenizing RWAs since 2018. Hendricks emphasized, “Tokenization is a critical component of the decentralized finance (DeFi) ecosystem, allowing assets like art, diamonds, and real estate to be fractionalized. Each token represents a percentage of the asset, enabling investors to own parts of high-value items and receive income from their use.”

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Advantages of Tokenized RWAs

Tokenizing RWAs offers significant advantages, particularly in terms of transparency and asset management. Hendricks highlighted, “We are seeing large financial institutions exploring how distributed ledger technology can enhance asset management functions.”

This trend is evident as BlackRock, the world’s largest asset manager, led a $47 million funding round for Securitize, a company focused on bringing physical and traditional financial assets onto the blockchain. Additionally, Mastercard announced a project aimed at improving cross-border settlements through distributed ledger technology, reducing errors and fraud.

AI: The Catalyst for Tokenized RWA Use Cases

Experts believe AI will play a pivotal role in advancing RWA tokenization. Meysam Alizadeh, Senior Researcher at the Digital Democracy Lab at the University of Zurich and CEO of Coinfident, noted, “AI can revolutionize RWA token trades by enabling asset value prediction. For instance, AI can forecast the future values of assets in a venture capitalist’s portfolio, improving the valuation of RWA tokens.”

Jacques Voorhees, CEO and Founder of RealCap, shared insights on using AI for predictive pricing. “When we started tokenizing diamonds, we didn’t need AI for price predictions. But for RWAs with less available pricing information, AI is essential to determine accurate prices.”

RealCap’s AI solution, “virtual fungibility,” enhances the tradability of tokenized RWAs by minimizing price discrepancies. Voorhees explained, “Investors need an objective measure for pricing, and AI can provide predictive prices for unique assets like art.”

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Streamlining RWA Workflows with AI

AI’s potential extends to automating RWA workflow analysis. Alizadeh pointed out, “One of the risks of RWA tokenization is smart contract vulnerabilities. AI can create reliable smart contracts, streamline reviews, and detect potential bugs and compliance issues.”

Natalia Karayaneva, CEO and Founder of Propy, described how her company uses AI to enhance real estate transactions. “Propy AI reads purchase agreements, creates transaction trackers, and sets intelligent deadlines, ensuring a smoother, secure, and transparent property investment process.”

AI also plays a role in customer risk analysis. Alizadeh added, “AI can evaluate borrower credibility based on past on-chain transactions, similar to credit scoring in traditional finance.”

Challenges and Considerations

Despite AI’s promise, challenges remain. Alizadeh cautioned, “AI requires data to function effectively, and limited data access can hinder its usability. Moreover, decentralized exchanges often lack comprehensive KYC procedures, complicating customer risk assessment.”

Regulatory issues and asset verification also pose significant hurdles. Alizadeh remarked, “Tokenizing assets like buildings could classify them as securities, attracting regulatory scrutiny and decreasing incentives for RWA tokens. Additionally, verifying the authenticity of assets backing RWA tokens remains challenging.”

The Road Ahead

To navigate these challenges, tokenized RWAs must be carefully structured. Hendricks explained, “Many RWA offerings in DeFi are debt or loan instruments, where investors provide collateral in exchange for interest. This model is lightly regulated but requires rigorous KYC and AML procedures to ensure compliance.”

Ultimately, the integration of AI with blockchain technology holds immense potential to revolutionize asset management and trading. By addressing regulatory, data, and verification challenges, AI-driven RWA tokenization can democratize access to investment opportunities and transform traditional financial systems.

As Hendricks aptly put it, “The future of finance lies in the seamless integration of AI and blockchain, paving the way for a more transparent, efficient, and inclusive financial ecosystem.”