An AWS exec details how firms like JPMorgan and Millennium are using data analytics in the public cloud as Wall Street leans more into the tech

  • The data Wall Street firms rely on is increasingly migrating to the public cloud.
  • The shift comes as Wall Street firms experiment with the benefits of analyzing data in the cloud. 
  • AWS exec John Kain discussed how firms like JPMorgan and Millennium are leveraging the cloud provider’s analytics.
  • See more stories on Insider’s business page.

Wall Street has always been a place driven by information. Where data goes, firms are likely to follow. 

And for financial data providers, the latest frontier is the public cloud.

Some of the biggest sellers of data, like Bloomberg and Nasdaq, are now offering real-time data via the cloud. At the same time, banks and hedge funds are putting more resources towards handling data in the cloud.

And it’s a trend that is showing no signs of slowing down as Wall Street gets more ambitious with its use cases for data, John Kain, AWS’ worldwide business development leader of capital markets and banking, told Insider.

“That ability to have all that data at your fingertips in the cloud is compelling,” Kain said.

“Where you’ve seen most of the adoption is on the analytics and risk perspective. You see a lot of those big calculations, quite common across the industry, and I think that’ll continue to take hold.”

To address that growing trend, AWS recently launched a service that enables financial companies to better aggregate, organize, and analyze data quickly in the public cloud. 

Amazon FinSpace allows users to integrate separate data catalogs into one location, giving different teams the ability to search and find data across the organization. As a result, they can expedite the process of analyzing data with AWS tools and functions.

FinSpace can be used in conjunction with other AWS services, such as Amazon Redshift, a data warehouse service, and SageMaker, which allows data scientists to build, train and deploy machine-learning models.

Early adopters of the tech include consultant Deloitte, which uses FinSpace to process large amounts of data at scale and within its analytics sandboxes, which are environments outside of production where data scientists can deploy new techniques and analyses.

The public cloud has allowed firms to be more aggressive with their data strategy

Data science and management are becoming more core to financial institutions’ decision-making processes. As cloud providers like AWS, Microsoft Azure, and Google Cloud look to better serve their banking customers, resources continue to flow to services that strengthen those capabilities. 

A handful of financial data providers already funnel real-time data to the public cloud.

Nasdaq launched Nasdaq Cloud Data Services in April 2020 to allow real-time access to its exchange, index, and fund data. Meanwhile, data giant Bloomberg released B-PIPE globally on AWS in September 2019, expanding the reach and access of its ubiquitous Terminal market data. 

This April, trading venue Tradeweb moved US treasury and UK Gilt closing price data to AWS’ data exchange. 

“It’s been over the last couple of years that the intensity of data within financial services has become ever more critical,” Kain said. 

Firms are also looking beyond traditional financial data, using so-called alternative data, which includes using complex, often unstructured data sets to glean business insights or better understand risk, Kain said. 

And it’s not just the variety of data sets that is reinforcing the role of data in banking. The size of the datasets, the volatility in the markets, and the volume of trading activity — especially over the past year — have also underscored the importance of data and the ability to leverage the public cloud when analyzing it.

JPMorgan Chase is one such example. The bank has used AWS offerings for trading analytics (Amazon EMR) and risk calculations (AWS Lambda and Amazon Elastic Kubernetes Service) and is currently in the process of building out its AI system, OMNI AI, using AWS’ machine-learning toolkit, SageMaker. 

“The combination of a scalable AI platform and AWS’ elastic compute environments will help us accelerate our efforts to infuse analytics in everything we do,” Lori Beer, the bank’s chief information officer, said during AWS re:Invent 2020 in December.

Millennium Management is another firm thrusting data science into the center of its operations, Kain said. The New York-based hedge fund with more than $51.5 billion in assets under management used AWS tool SageMaker to allow portfolio managers to better analyze data sets with machine learning.

However, while JPMorgan and Millennium have significant budgets to dedicate to those efforts, the same cannot be said for other players across the Street.

A lack of resources among smaller institutions has been another barrier to unlocking data and analytics, Kain said, which led to the motivation to roll out FinSpace.

“Certainly FinSpace is ideal for that segment of customers that are really looking for a way to get quickly into the analytics and improve their analytics capability and not have to have a very deep level of cloud knowledge to be able to do that,” Kain said. 

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