Blockchain, distributed ledger technology, AI
The meteoric rise of AI over the past year has captured worldwide attention. With hundreds of millions of users flocking to tools like ChatGPT and the deluge of other AI-based applications, investors and startups have quickly shifted their focus, directing significant investments toward AI projects. This renewed interest has not been limited to Big Tech, it has also sparked curiosity in the world of decentralized finance.
Notable investors focused on crypto and blockchain, such as Framework Ventures and Peter Thiel’s Founders Fund, are now championing a new wave of “crypto + AI” projects like Sentient or Space & Time. While a large portion of these new cross-industry startups have focused on using crypto to challenge incumbent players in AI technology, we have yet to see more traditional financial institutions thinking about how the combination of AI and blockchains could play a role in their technology stack, that is until last month.
Recently, the team behind the leading Oracle protocol, Chainlink, released a report revealing that it was working on an initiative combining AI, oracles and blockchain technology to address the lack of real-time and standardized data on operations on titles.
Who’s Who of global MFI providers
The companies involved in the project are among the elite of global financial market infrastructure (FMI) providers, including Swift – the world’s largest interbank messaging platform and Euroclear – a global clearing and settlement company, as well as investment management companies such as Franklin Templeton and Wellington Management and major banks including UBS, CACEIS, Vontobel and Sygnum Bank.
Oracles are entities that provide services to blockchains, handling tasks that they typically cannot handle on their own, such as routing live real-world data or facilitating transactions across and between different blockchains. In the crypto industry, Chainlink is the most widely adopted Oracle network that has enabled a total transaction value of over $16 trillion through its data feeds and cross-chain interoperability protocol ( nicknamed “CCIP”), a bridge between the channels.
Financial institutions around the world face complex data fragmentation issues, including data on mergers, dividends, stock splits, and more. Data relevant to multiple parties in a transaction must often pass through a complex journey through the hands of custodians, brokers, fund managers, exchanges and investors.
As data moves through channels, it often enters various inconsistent formats and states (think PDFs, source press releases, spreadsheets, etc.), leading to a confusing array of sources, formats, terminologies, data cleansing issues and duplications or differences. clearly erroneous information. Specific processing of corporate actions is a decade-long problem that many, including giants like DTCC, have attempted to solve.
What may seem like a minor problem to an outsider is actually a major and complex problem in the world of post-trade finance: current inefficiencies in securities trading processes with thousands of regional investors, brokers and brokers. Custodian companies face costs of $3 million to $5 million. every year and 75 percent of companies have to revalidate the custodian and exchange data manually.
Chainlink’s initiative introduces a potential solution using decentralized blockchain oracles. The aim is to alleviate the need for manual reviews by creating a “unified gold record” around securities transactions that were carried on blockchains and accessed in real time by custodians, asset managers and other interested parties.
AI for data cleaning
Oracle Chainlink networks are used in combination with extended language models (LLMs) like OpenAI’s ChatGPT 4o, Google’s Gemini 1.5 pro, and Anthropic’s Sonnet Claude 3.5 to validate and deliver key financial data on the blockchain or in chain. On-chain securities transaction data is then moved between private and public chains using Chainlink’s CCIP.
“The combination of AI and oracles is a powerful tool for taking securities trading data and transforming it into structured data in a very reliable way,” said Sergey Nazarov, co-founder of Chainlink. “Solving this problem creates many benefits for asset managers, banks and financial market infrastructures to all be in sync many times faster than today, at a fraction of the cost and with a massive reduction in costly errors that affect the financial system.
So why is this initiative important?
According to Laurence Moroney, AI researcher and best-selling AI author, said in a written statement to Forbes: “While this project focuses on securities trading data, Chainlink’s approach to combining AI , oracles and blockchains can be applied to other types of unstructured data. in financial services and beyond.
The possibilities are extensible if this approach is applied to other types of unstructured data. Most of the world’s human-generated information, such as legal documents, insurance contracts, real estate contracts, surveys, voice recordings, and social media posts, is not easily readable by people. machines. The potential impact is significant and can transform the way industries manage everything from contracts to customer interactions, including using AI.
In industries like financial services, where much of the data remains unstructured, this solution may not yet be the silver bullet as significant hurdles remain. LLMs are still prone to hallucinations, which means they can still generate inaccurate or fabricated information. In fact, one study comparing 11 public LLMs showed rates of hallucinations ranging from 3 to 27 percent. To minimize the risks of LLMs, a pre-trained model is likely necessary for true scaling, ensuring that the system is well equipped to handle complex and nuanced datasets.
Even with oracles verifying results via a consensus-based model and the use of multiple LLMs, there must be mechanisms in place to flag uncertainty around results that trigger manual review, particularly in high-speed environments. high stakes like finance, where many investors make compromises. their decisions based on this data. Many specialists are also now focusing on Small Language Models (SLM), curated and better structured data, especially for regulated companies.
The new plumbing
For the powerful combination of AI and blockchain to truly gain traction in a way that is both impactful and sustainable, institutions must find practical applications for blockchain technology. Often, these applications will be in the form of key, mission-critical operational systems and processes.
As Stéphanie Lheureux, director of the Digital Assets Competence Center at Euroclear, pointed out, the combination of oracles and AI “can solve major problems and rethink workflows for greater efficiency, transparency and value.” .
At the very least, this initiative demonstrates that some of the most significant innovations may be those occurring quietly behind the scenes, solving complex and inglorious problems at the large financial institutions that power the global financial services industry.
Digital Financial Markets Infrastructure (dFMI) is not the most interesting topic for consumers, businesses and policymakers – few people are enthusiastic about having to replace old plumbing with new – but it is an essential digital transformation that will allow our money to flow freely for longer. individuals and businesses, at lower cost, with better products, services and accuracy on Web3 for the 21st century and in the future.
