TLDR
- With the launch of a data standardization program, Chainlink aims to innovate the processing of corporate actions data through AI and blockchain technology.
- Big names in the financial sector, such as Euroclear, Swift, and Franklin Templeton, are among the key participants in this initiative.
- The initiative creatively employs AI language models and oracle technology to manage complex, unstructured data.
- This project sets out to slash operational costs for financial institutions, which currently range from $3 to $5 million each year per firm.
- The initial stage of this project zeroes in on equity and fixed-income data from six different European countries.
Chainlink They have started a novel project with the goal of standardizing the processing of corporate actions data by partnering with leading financial institutions, such as Euroclear, Swift, and Franklin Templeton.
This project utilizes AI and blockchain to tackle the long-standing disjointed method of corporate data distribution worldwide.
We are thrilled to share the outcomes of a collaborative corporate actions initiative involving Chainlink, Euroclear, Swift, and six major financial institutions.
We’ve successfully shown how a blend of AI, oracles, and blockchain can tackle the chronic issue of unstructured data in financial sectors. pic.twitter.com/4YOT5tX2sr
— Chainlink (@chainlink) October 21, 2024
The main focus of this initiative is to refine the processing and delivery of corporate actions like mergers, dividends, and stock splits across the finance industry.
These crucial pieces of information are found in disparate formats around the world, resulting in inefficiencies that cost individual financial institutions $3 to $5 million yearly.
“Converting scattered corporate actions data into cohesive ‘golden records’ for reliable, singular truth among market participants marks a significant leap forward,”
stated Sergey Nazarov, Chainlink’s co-founder, during an announcement of the project at the SmartCon conference in Barcelona.
The initial focus targets data related to equity and fixed-income securities in six European nations. Chainlink uses a groundbreaking method by merging decentralized oracles with various large language models such as OpenAI’s ChatGPT, Google’s Gemini, and Anthropic’s Claude.
These AI frameworks collaborate to extract and process data on corporate actions from multiple unstructured sources. such as PDFs and press releases.
The technological setup turns raw information into standardized 'Golden Records' that meet international financial norms like ISO 20022 and Securities Market Practice Group guidelines, and then distributes them across varied blockchain networks via Chainlink’s Cross-Chain Interoperability Protocol (CCIP), guaranteeing uniform and precise data throughout.
Mark Garabedian, who oversees digital assets and tokenization strategy at Wellington Management, highlighted the potential gains in efficiency:
“Utilizing AI and Chainlink oracles to interpret and align high-value, unstructured data can greatly reduce the need for manual intervention, offering significant efficiency and cost benefits.”
A noteworthy array of financial institutions, including UBS, CACEIS, Vontobel, and Sygnum Bank, have joined the project. Contributions are also made by blockchain ecosystems like Avalanche (AVAX), ZKsync (ZK), and Hyperledger Besu.
The issue of fragmented corporate actions data is particularly pressing in European markets, where information is scattered across several jurisdictions and in different forms.
Present systems depend heavily on manual workings, leading to delays, mistakes, and high operational expenses. Chainlink’s approach aims to automate, thereby minimizing errors and speeding data dissemination.
Future project phases will focus on integrating current financial infrastructure, including Swift messaging norms, to foster greater adoption across the industry.
Such integration is essential to ensure the new system meshes smoothly with established financial frameworks while boosting efficiency and accuracy.
This initiative marks a critical advance in updating financial market infrastructure. By combining AI and blockchain, Chainlink and collaborators are confronting one of financial data management's longstanding issues.
Standardizing corporate actions data has the potential to make markets more efficient, cut down on operational costs, and better the accuracy of financial data handling.
Recent progress includes successful pilots, showing the method's adeptness at processing intricate corporate actions data spanning multiple jurisdictions.
The initial phase of the initiative has yielded favorable results in both minimizing processing time and boosting data precision, as noted by the involved parties.
The project team is currently concentrating on broadening the system’s functionality and enrolling more financial entities. There is also an effort to augment AI models for handling increasingly sophisticated corporate actions data while upholding accuracy.
