J.P. Morgan has added Containerized Data for institutional investors to its Fusion data mesh. The solution normalises data across multiple providers, sources, types and structures and provides consistent and enriched data across business services.
Fusion is a cloud-native data technology platform that provides data management, analytics and reporting, and is built on J.P. Morgan’s global operating model and data foundation. It transforms and links data, making it interoperable and ready for AI and ML applications. Investors can access data in consistent containers using cloud-native channels including APIs, Jupyter notebooks, Snowflake and Databricks.
Containerized Data is available for data types and sources such as custody, fund accounting and middle office data from J.P. Morgan and additional providers. Clients receive data that looks and feels the same across sources and is ready for analysis and integration into their workflows. They can also extract maximum value as the data is harmonised across both public and private assets. An enhanced data catalog, data dictionary and semantic layer provide the foundations for AI and ML implementation.
Jason Mirsky, head of data solutions at Securities Services, says: “We understand institutional investors’ nuanced data challenges. With Containerized Data, we’re addressing the most pressing needs we hear from our clients. Our financial data expertise, vast reference data universe and strategic industry collaborations enable us to model data in ways that other firms can’t, solving unique data frustrations for clients.”
Containerized Data includes data ingestion that normalises data making it ready to be used across investors’ operating models; a complete portfolio view across business services based on linked data in Fusion; a data explorer to view, filter and drill down into securities services data; and data mesh that allows Fusion to simplify data consumption and enable clients to access their Containerized Data anywhere at any time.
Subscribe to our newsletter
