AI and Blockchain: The Next Frontier in Financial Innovation

The last year has marked an explosive growth in artificial intelligence (AI), capturing widespread attention and transforming the tech landscape. Tools like ChatGPT have attracted millions of users, rallying startup investors to pivot swiftly towards AI-focused projects. This enthusiasm isn’t limited to tech giants; it’s also sending ripples through the realm of decentralized finance (DeFi), where innovative ties between crypto and AI are forming.

Leading the charge are influential investment groups such as Framework Ventures and Peter Thiel’s Founders Fund, promoting an exciting blend of “crypto + AI” projects. Startups like Sentient and Space & Time are at the forefront of this revolution, driven by the ambition to leverage crypto technology against established AI players. However, until recently, traditional financial institutions had been slower to explore the interplay between these cutting-edge technologies—until Chainlink unveiled a groundbreaking initiative last month.

A Powerful Coalition of Financial Giants

Chainlink, a prominent oracle protocol known for bridging on-chain and off-chain data, has gathered a formidable coalition of global financial market infrastructure (FMI) providers for its latest project. This group boasts heavyweights such as Swift, the largest inter-bank messaging service in the world, and Euroclear, a leader in global clearing and settlement. They’ve enlisted notable investment management firms like Franklin Templeton and Wellington Management, alongside major banks including UBS, CACEIS, Vontobel, and Sygnum Bank.

But what exactly are oracles? Simply put, they are intermediaries that enable blockchains to interact with external data sources. In the crypto sphere, Chainlink stands out as the most widely adopted oracle network, powering over $16 trillion in transactions and facilitating seamless interoperability between different blockchains.

Tackling Data Fragmentation in Finance

The financial industry is no stranger to data fragmentation, especially when it comes to corporate actions such as mergers, dividends, and stock splits. Often, this critical data must navigate a convoluted chain of custodians, brokers, fund managers, exchanges, and investors, leading to a muddled mix of inconsistent formats—think confusing PDFs and messy spreadsheets. This issue has plagued financial institutions for years, prompting efforts from major entities like DTCC to find effective solutions.

In fact, the stakes are high here. It’s estimated that inefficiencies in processing corporate actions can cost firms anywhere from $3 to $5 million annually, with around 75% of companies manually revalidating custodial and exchange data. Recognizing this challenge, Chainlink is introducing a fresh perspective: decentralized blockchain oracles aimed at creating a "unified golden record" of corporate actions readily accessible in real-time.

AI: The Data Cleanup Crew

To elevate the efficiency of corporate actions data management, Chainlink plans to integrate its oracle network with large language models (LLMs) such as OpenAI’s ChatGPT, Google’s Gemini, and Anthropic’s Claude. This collaboration aims to validate financial data before moving it onto blockchain networks, both public and private, utilizing Chainlink’s Cross-Chain Interoperability Protocol (CCIP).

Sergey Nazarov, Co-Founder of Chainlink, highlighted the advantages of this integration: “Combining AI and oracles creates highly reliable structured data from corporate actions. The result? Asset managers and banks can execute transactions significantly faster and at a fraction of the traditional costs, minimizing errors that could disrupt the financial system.”

Beyond Corporate Actions: A Broader Impact

While the initial focus is on corporate actions, this blend of AI, oracles, and blockchain technology holds the potential to revolutionize other domains within financial services and beyond. Laurence Moroney, an AI researcher and bestselling author, pointed out that the method Chainlink is using could extend to various types of unstructured data—think legal contracts, insurance policies, and customer interactions.

However, challenges remain, especially given that large language models can produce inaccuracies or "hallucinations." A recent study indicated that such models can generate false information 3% to 27% of the time. Hence, pre-trained models will be necessary for scaling this solution effectively, especially in a field as crucial as finance where accuracy is non-negotiable.

The New Plumbing of Finance

For AI and blockchain to generate lasting impact, financial institutions need to identify real-world applications that can build operational efficiencies. Stéphanie Lheureux, Director of the Digital Assets Competence Center at Euroclear, noted that leveraging oracles alongside AI can address significant pain points, enhancing workflows and overall value.

While discussions around digital financial market infrastructure (dFMI) might not be as flashy as new consumer technologies, they represent vital shifts within the financial sector. As these behind-the-scenes advancements take shape, they promise to facilitate smoother operations, lower costs, and more reliable services in a digital economy increasingly driven by Web3 principles.

The AI Buzz Hub team is excited to see where these breakthroughs take us. Want to stay in the loop on all things AI? Subscribe to our newsletter or share this article with your fellow enthusiasts.