In an era where financial markets operate around the clock and data volumes have increased accordingly, asset managers are accelerating their pivot to cloud-based solutions for market data delivery. A study released by SIX, the Swiss-based global financial information provider, and Crisil Coalition Greenwich reveals that this transformation has hit new levels.
The research underscores how artificial intelligence and machine learning are pivotal forces propelling this shift.
With 80% of asset managers viewing AI/ML as a key driver for market data consumption over the next two years, the industry is poised for a data evolution that aims for efficiency, scalability, and innovation.
The study’s findings paint a picture of ongoing evolution.
Cloud adoption has surged dramatically: 63% of survey participants now receive market data via internet connectivity from public cloud platforms, a stark leap from just 30% in 2023.
This acceleration reflects a broader embrace of hybrid and multi-cloud environments, enabling firms to handle the deluge of real-time information without the constraints of legacy on-premises systems.
Matthew Nurse, Head of Market Data at SIX’s Financial Information division:
“The rapid uptake of AI/ML, combined with the growing reliance on cloud infrastructure and real-time delivery, is evidence of a clear shift toward more scalable, flexible, and cost-effective delivery models.”
At the core of this momentum is AI and ML’s role in unlocking data’s full potential.
These technologies are automating data ingestion, cleansing, and analysis, allowing asset managers to derive actionable insights at speeds unattainable through traditional methods.
The 80% figure isn’t mere optimism; it signals a consensus that AI/ML will optimize everything from predictive analytics to algorithmic trading.
For instance, machine learning models can now forecast market volatility by sifting through petabytes of historical and live data, all hosted seamlessly in the cloud.
This integration is particularly transformative for buy-side firms, where 53% of respondents anticipate cloud enhancements in streaming data delivery—critical for high-frequency trading and 24/7 asset classes like cryptocurrencies.
As global trading hours extend beyond traditional boundaries, real-time data usage has ballooned, with 65% of participants leveraging it throughout the entire trading day for risk management, compliance, and portfolio optimization.
Yet, this cloud ascent isn’t without hurdles.
The study highlights persistent challenges in data governance amid a labyrinthine regulatory landscape.
As firms ingest diverse data streams—from indices and risk metrics to emerging crypto feeds—ensuring accuracy and compliance becomes paramount.
Over three-quarters of buy-side respondents are clamoring for expanded access to historical tick data to bolster market surveillance and trade reconstruction, underscoring the need for robust archival capabilities in cloud setups.
David Easthope, Senior Analyst for Coalition Greenwich Market Structure & Technology says,
“Firms will need to focus on developing robust data management practices to ensure the quality and accuracy of data.”
Cybersecurity threats and vendor lock-in also loom large, as does the skills gap in AI implementation.
Smaller asset managers, in particular, may struggle with the upfront costs of migration, even as cloud’s pay-as-you-go model aims for long-term savings.
The benefits, however, far outweigh these obstacles.
Cloud’s elasticity supports dynamic workloads, slashing latency and costs while fostering collaboration across global teams.
Market data vendors are stepping up as enablers, with firms increasingly favoring vendor-fed systems over direct sourcing for their reliability and integration ease.
This vendor reliance is fueling a projected uptick in spending: nearly 70% of participants expect budget increases of 1% to 5% over the coming year, targeting high-growth areas like index data, regulatory feeds, and crypto analytics.
Looking ahead, the study forecasts a data ecosystem where AI/ML and cloud converge to democratize access.
Asset managers who invest now could gain a competitive edge in an AI-augmented environment.