Chainlink 与主要金融机构合作，利用人工智能和区块链改进企业行为数据报告

报告称，企业行为数据的自动化和标准化可以帮助显着降低运营效率低下的情况，目前每年由于错误和手动数据处理而导致企业损失数百万美元。

Data provider Chainlink (LINK), together with major financial market participants, announced Monday an initiative to enhance the accessibility and standardization of corporate actions data using AI and blockchain technology.

数据提供商 Chainlink (LINK) 与主要金融市场参与者周一宣布了一项计划，旨在利用人工智能和区块链技术增强企业行为数据的可访问性和标准化。

Chainlink, Euroclear, Swift and Franklin Templeton, among other participants, started an integration to make corporate actions data more widely available and standardized using artificial intelligence and blockchain tech.

Chainlink、Euroclear、Swift 和 Franklin Templeton 等参与者开始整合，利用人工智能和区块链技术使企业行为数据更广泛地可用和标准化。

The project aims to address a long-standing challenge: the lack of standardized and real-time data for corporate actions such as mergers, dividends and stock splits. This data, which is used by investors to track changes in their portfolios, is currently fragmented in markets like Europe.

该项目旨在解决一个长期存在的挑战：缺乏合并、股息和股票分割等企业行为的标准化和实时数据。投资者用来跟踪其投资组合变化的这些数据目前在欧洲等市场是分散的。

"Turning various pieces of disconnected corporate actions data into unified ‘golden records’ that can then be relied on by hundreds of market participants as a definitive, single source of truth is truly a huge step forward," Chainlink co-founder Sergey Nazarov said. "This will help financial markets synchronize faster, reduce errors and cut costs."

Chainlink 联合创始人谢尔盖·纳扎罗夫 (Sergey Nazarov) 表示：“将各种互不相关的企业行为数据转变为统一的‘黄金记录’，然后数百名市场参与者可以将其作为确定的、单一的事实来源，这确实是向前迈出的一大步。” “这将有助于金融市场更快地同步、减少错误并削减成本。”

The initiative's first phase focused on equity and fixed-income corporate actions data in six European countries. Chainlink connected its decentralized oracles with large language models (LLMs) to extract corporate actions data from various sources and transform it into a structured format.

该计划的第一阶段重点关注六个欧洲国家的股票和固定收益公司行动数据。 Chainlink 将其去中心化预言机与大型语言模型 (LLM) 连接起来，从各种来源提取公司行为数据并将其转换为结构化格式。

The decentralized oracles, which provide data from the outside world to smart contracts on different blockchains, were integrated with LLMs from OpenAI, Google and Anthoptic to extract data from various sources, including press releases, legal filings and financial news articles. This data was then transformed into a structured format, called "Golden Records," that complies with global financial standards.

这些去中心化的预言机将外部世界的数据提供给不同区块链上的智能合约，并与 OpenAI、Google 和 Anthoptic 的法学硕士集成，以从各种来源提取数据，包括新闻稿、法律文件和财经新闻文章。然后，这些数据被转换为符合全球金融标准的结构化格式，称为“黄金记录”。

Later stages will explore ways to integrate this framework with existing financial systems for broader industry adoption, the report said.

报告称，后期阶段将探索如何将该框架与现有金融系统相结合，以供更广泛的行业采用。

Participants in the initiative include Euroclear, Swift, UBS, Franklin Templeton, Wellington Management, CACEIS, Vontobel and Sygnum Bank. Blockchain ecosystem partners Avalanche (AVAX), ZKsync (ZK) and Hyperledger Besu networks also contributed.

该计划的参与者包括 Euroclear、Swift、UBS、Franklin Templeton、Wellington Management、CACEIS、Vontobel 和 Sygnum Bank。区块链生态系统合作伙伴 Avalanche (AVAX)、ZKsync (ZK) 和 Hyperledger Besu 网络也做出了贡献。

"We're excited about the potential of this collaboration to improve the timeliness, accuracy, and efficiency of corporate actions data dissemination," said Francois Masquelier, Euroclear's head of digital initiatives. "This could ultimately benefit a wide range of market participants, including investors, brokers, and custodians."

Euroclear 数字计划主管 Francois Masquelier 表示：“我们对此次合作在提高企业行为数据传播的及时性、准确性和效率方面的潜力感到兴奋。” “这最终可能使广泛的市场参与者受益，包括投资者、经纪人和托管人。”