Emerging Technologies Reinvent Market Data
Market data consumption is getting a fresh look as new technologies are enabling participants to access more data in real time, determine what they want to consume when and how, and evolving new use cases faster, according to participants at the Coalition Greenwich webinar titled Emerging Technologies Set to Unlock the Full Potential of Market Data. The webinar was hosted by Coalition Greenwich Head of FinTech Research David Easthope.
“Data is a nuanced thing. The beautiful thing about data provisioning is not only can you pick exactly what you want, you can pick the timeliness you need and get it delivered when and where the new technologies will allow it,” stated Matthew Nurse, Commercial Product Director at leading market data provider, SIX.
Growing Demand for Real-Time Data
The second edition of a global market data study by Coalition Greenwich in partnership with SIX shows that while data quality—in terms of accuracy, coverage and feed availability—continues to trump cost, demand for real-time data is growing as more players move more processes intraday. Simultaneously, historical tick data consumption is increasing as well.
Half the study participants said they use real-time data throughout the day now. “Just like our lives are in real time, SIX sees a big uptick in demand for real-time data,” said Nurse.
Crucially, its use is extending beyond traditional trade execution to areas such as market abuse, transaction cost analysis and arrival price, revealed the study. Moreover, given the overlay between data and technology, market participants are making conscious choices about their data delivery mechanism today. “This has a deep impact on cost and timeliness of data,” said Nurse.
New-Age APIs as Preferred Data Delivery Mechanism
Three factors were cited by 70% of the study participants supporting their preference for advanced APIs as their data delivery mechanism: the need to integrate data as quickly as possible, the return on investment and the effort required to maintain the interface.
“With APIs, customers are being given the keys. They are in control of how they put in the data and what they do with it once it's in the building,” said Henk D’Hoore, Head of Product Development at SIX.
However, the use case should drive the delivery mechanism, he said. For instance, SIX has identified two use cases for APIs. Its Web API, launched last year, enables a display tool for market data so that players can take intelligence-backed decisions quickly. This “request response” API is “differently built” from the upcoming Bulk API, which can initialize and feed databases with high-volume static data.
“We want data to be democratized so the average user can make better investment decisions… It’s fantastic for us to see these applications being launched by our customers [in ways] that benefit the end user,” said D’Hoore.
New Frontiers in Tech-Data Interplay
The financial markets have always been quick to adopt new technologies from APIs and cloud computing to artificial intelligence and machine learning (AI/ML). Now, 75% of the study’s respondents are keeping an eye on generative AI for future impact on market data.
GenAI is moving beyond the hype, asserted Jennifer Chang, Head of Innovation Hub at SIX. “We are seeing some real use cases that are bringing value.”
Early GenAI experiments focused on internal security, efficiencies and knowledge bots. “One year down the line, not only have our customers successfully implemented bots [on] productivity and efficiency, but they have also moved along to look at use cases that are closer to their value proposition … [of] improving investment decisions,” she said.
Apart from using “essential AI” for completeness and accuracy of data coverage and “AI enrichment” to enhance its products and services, Chang is excited about the “game-changing” use of the new capabilities provided by AI to “revolutionize the customer experience. This is just the beginning; exciting times lie ahead.”
Technology Can Enable Cost Controls
Undoubtedly, rising costs are a driving factor in data consumption. But factors like data quality, and time and mode of delivery influence costs.
Every use case may not need the highest-quality data, said Nurse, pointing to the professionalization of data understanding with institutions. “More people are trying to understand what quality of data they need. This is where web APIs are perfect as you can switch on, switch off, choose what you need and how quickly. This sensitivity means that cost controls for certain areas should get easier.”
Looking Ahead
Nurse expects transparency on data and cloud costs to improve, and commercial models to evolve.
As for GenAI, despite risks of erroneous data and high implementation costs, it is here to stay. Asserted Chang, “Research is meeting reality now with real use cases.” However, data users must “be brave enough to experiment and willing to fail,” said D’Hoore, because only when they play around with market data technologies will they “understand what you can use it for and why not.”