转型在即：2026年五大关键公司行为趋势

Core Viewpoint - The article emphasizes the growing importance of corporate action data as a strategic asset for financial services institutions, particularly in trading, risk management, and customer interaction. The focus on extracting value from this data is expected to accelerate transformation in the coming year [1][2]. Group 1: Standardization of Corporate Action Data - Most corporate action data is still published in unstructured formats (e.g., PDF, HTML), making extraction a manual task, which increases processing time and market risk. There is a pressing need to reduce latency in corporate action data to enhance its application in trading and risk management [3]. - The ISO 20022 standard, which aims to replace the widely used ISO 15022 standard, is seen as the ultimate goal for corporate action data standardization. SWIFT has mandated the use of ISO 20022 for cross-border payments and plans to adopt it for corporate action messaging in the EU and UK by 2030 [3]. Group 2: Demand for Debt Corporate Action Data - There has been a significant increase in demand for corporate action data related to debt instruments due to the surge in fixed income investments. This data is essential for supporting middle and back-office functions, as well as for trading and portfolio optimization [4][5]. Group 3: Reducing Latency in Corporate Action Data - The market is increasingly focused on minimizing the time lag between corporate actions and data transmission, with some traders in the Asia-Pacific region aiming for a latency of just one hour. The shift towards T+1 settlement cycles in various regions is driving this demand for lower latency [6]. Group 4: Expanding AI and Machine Learning Applications - AI and machine learning models are being utilized to optimize the collection, processing, and validation of corporate action data, which is expected to grow significantly in the coming years. This will help reduce reliance on manual intervention and minimize operational risks associated with non-standard data formats [7]. Group 5: Focus on Value-Driven Corporate Action Data - The emergence of new applications, such as alpha generation, along with the transition to T+1 settlement cycles, is accelerating the transformation of the corporate action data landscape. Increased use of AI and machine learning, along with widespread standardization, will help achieve near real-time data transmission [8][9]. Future Outlook - LSEG's corporate action data is recognized for its high quality and comprehensive coverage, processing millions of corporate events annually. The company aims to continue expanding its coverage of event types and asset classes while leveraging AI to streamline data workflows [11].