Chainlink has launched a groundbreaking initiative in collaboration with major financial institutions including Franklin Templeton, Swift, and Euroclear, aimed at revolutionizing corporate actions data management.

This initiative seeks to standardize the collection and distribution of corporate actions data, such as mergers and dividends, which is currently fragmented across various countries.

Chainlink's oracles will quickly scan diverse sources for relevant information, significantly reducing the need for manual reviews and enhancing data accuracy.

Co-founder Sergey Nazarov emphasized that this initiative will transform error-prone corporate data into a reliable single source of truth, enhancing efficiency across the finance sector.

Future phases will explore integration with existing financial systems, such as Swift messaging standards, to enhance industry adoption and operational efficiency.

Key participants in this initiative also include UBS, Wellington Management, CACEIS, Vontobel, and Sygnum Bank, all contributing to the project's ambitious goals.

By addressing inconsistencies in data structure, format, and standards, the project aims to provide a unified, real-time 'golden record' of corporate actions data.

The initiative will aggregate corporate data onto a blockchain, creating this 'golden record' that consolidates vast amounts of data in real-time.

Current inefficiencies in corporate action processes cost regional businesses approximately $3 to $5 million annually, with 75% of firms relying on manual data re-validation.

The first phase of the project focuses on corporate actions data for equity and fixed-income securities in six European countries, utilizing large language models to extract and standardize data.

This integration allows for near real-time distribution of corporate actions data across three blockchain networks, showcasing the project's innovative capabilities.

Specific large language models employed include OpenAI's ChatGPT 4o, Google's Gemini 1.5 pro, and Anthropic's Claude 3.5 sonnet.