JPMorgan launches Securities Services Data Mesh


J.P. Morgan today announced the launch of its Securities Services Data Mesh for institutional investors, available through Fusion by J.P. Morgan (Fusion).

The solution enables investors to retrieve critical investment data held by J.P. Morgan’s Custody, Fund Accounting and Middle Office services, using cloud-native channels including REST APIs, Jupyter notebooks and the Snowflake Financial Services Data Cloud.

Organizations aiming to take advantage of the cloud’s elasticity and tap into the accelerated growth and rapid development in analytics, AI and machine learning require data within a modern technology stack that is ready to use and analyze. Fusion supports investors in this journey with the release of the Data Mesh, which now includes Securities Services data for the first time. By providing a range of cloud-native channels, Fusion is addressing long-experienced pain points in integrating asset servicing data including the challenges to ingest data at scale, especially as portfolios and investments grow in size and complexity.

Gerard Francis, Head of Data Solutions, J.P. Morgan said, “Institutional investors continue to leverage data at an increasing rate to maximize alpha and operational efficiency. Having easy access to that data is paramount. With Fusion’s new Data Mesh, we meet our clients where they are, delivering data directly to their Snowflake instances and Python notebooks. Clients can now access data directly from applications running in the cloud and on-premise through Fusion APIs and other modern delivery channels. This launch is the latest example of Fusion helping clients to overcome their data challenges.”

Fusion is collaborating with leading cloud providers, including Snowflake, as part of this new offering to deliver Securities Services data directly into investors’ workflows.

“J.P. Morgan’s Fusion platform is transforming the client experience by modernizing how their clients access Securities Services data and analytics, fueled by the power, scale and secure data sharing of the Snowflake Financial Services Data Cloud,” said Benoit Dageville, Snowflake Co-Founder and President of Products.

Tim Fitzgerald, Global Head of Securities Services, J.P. Morgan said, “The Securities Services industry has become increasingly data-driven. Fusion is a central tenet of our offering, and its expansion to cloud-native delivery of custody, fund accounting and middle office data gives our clients the tools to focus on the evolution and growth of their businesses.”

Julia Hegelstad, Digital Product Manager at Storebrand Asset Management, said, “We have found the Fusion platform to provide a stable, modern and reliable way to connect into the J.P. Morgan’s Securities Services data universe. We were able to establish secure connectivity between Fusion and our proprietary code base within hours. Storebrand is looking forward to expanding the use of Fusion as the platform extends to new areas.”

New cloud-native capabilities and channels:

Fusion is Snowflake compatible with Securities Services datasets ready to be extracted directly from Snowflake tables. Investors using cloud services such as Snowflake as an integration layer can directly access J.P. Morgan data regardless of their cloud provider.

The new REST API, Python and Java SDKs enable investors to easily integrate their data into their workflows or existing applications and develop advanced analytics for a wide range of use cases, from automated reconciliation to investment analysis and reporting.

Investors can access data directly in their Jupyter notebooks using the Fusion Python library, allowing them to jump straight into analysis and work with the data to solve a vast spectrum of use cases with minimal effort.

The Data Mesh is optimized for developers with a notifications service that informs applications when key data events occur, self-service tools for application management and data delivery, and access to data catalogs and data dictionaries through the API and the Fusion UI.


By on Wed, 11 Oct 2023 09:49:00 GMT
Original link