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Articles / mica-regulation / AI, Machine Learning Will Drive Market Data Consumption

AI, Machine Learning Will Drive Market Data Consumption

AI/ML Impact on Market Data Delivery
80%
Percentage of asset managers who view AI and ML as key drivers over the next two years.
Real-Time Data Usage
65%
Percentage of respondents using real-time data throughout the trading day.
Cloud Data Connectivity Adoption
63%
Percentage of participants using public cloud for data connectivity, up from 30% in 2023.

⦿ Executive Snapshot

  • What: A report highlights AI and machine learning's growing impact on market data consumption among asset managers.
  • Who: SIX, Crisil Coalition Greenwich, asset managers, wealth managers, private banks.
  • Why it matters: The findings underscore a significant shift in data consumption practices, driven by technological advancements and the need for real-time data in a 24/7 trading environment.

⦿ Key Developments

  • 80% of asset managers view AI and ML as key drivers of market data delivery over the next two years.
  • 65% of respondents use real-time data throughout the trading day, influenced by the rise of 24/7 trading.
  • Almost 70% of participants expect a budget increase of 1% to 5% for market data, particularly in index, risk, regulatory, and crypto data.
  • 63% of participants now use public cloud for data connectivity, up from 30% in 2023.
  • 53% of respondents believe that cloud will enhance the delivery of streaming data.

⦿ Strategic Context

  • The increasing integration of AI and ML in capital markets reflects broader trends toward automation and efficiency in financial operations.
  • The shift from direct-from-source data to reliance on market data vendors signifies evolving preferences in data sourcing and delivery models.

⦿ Strategic Implications

  • Immediate implications include enhanced data delivery capabilities, enabling firms to make more informed investment decisions and manage risk effectively.
  • Long-term, the focus on AI/ML and cloud infrastructure could reshape market data management practices, requiring firms to invest in robust data governance.

⦿ Risks & Constraints

  • Potential risks include challenges in data quality and accuracy as firms adapt to new technologies and seek diverse data sources.
  • Regulatory complexities may pose obstacles, necessitating firms to develop comprehensive data management practices to navigate compliance effectively.

⦿ Watchlist / Forward Signals

  • Future developments in AI/ML applications in market data and cloud infrastructure adoption will be crucial to monitor.
  • Increased spending on market data and shifts in data sourcing strategies will signal firms' adaptation to the evolving landscape.
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