The data and data infrastructure landscape is always changing and evolving, and it can be felt especially keenly in the asset management industry. Sources and volumes of data are growing, with inconsistent standards and quality. Alternative and ESG data are now staples. Data warehouses and lakehouses now sit alongside data fabrics and data meshes.
Trying to keep up with software and best practices is challenging, and it often comes with a long projects and large price tags, things that are not core to the asset management business. And legacy companies provide solutions that are overly complicated to implement and are expensive to maintain.
Fencore provides platforms that are built specifically to support asset managers and their use cases, and work with any of their existing architecture. Our highly interoperable systems are equipped with universal connectors that integrate smoothly with existing systems, and accept a wide variety of data formats and database types. Data lineage, audit trails, and 4-eye approval workflows are built in.
Savings for customers are made via intelligent design that greatly lower the time spent on configuring and running data operations, and thereby reducing the costs of implementation and maintenance as well. This makes our platforms highly viable to gain ROI on smaller use cases, or firms with smaller operations as well.
Datahub – our flagship enterprise data management platform
FenDQ – a lightweight and robust data quality engine
FenRecon – a dedicated reconciliation engine
Fencore’s products were designed by ex-CADIS/Markit EDM team members, and were intended to overcome the inherent issues with many existing data management technologies, as well as to fit the unique requirements of financial institutions and make implementation projects as pain free as possible.
Our products are also designed with sympathy for the difficulties of incorporating new technology into organisations, and therefore range from comprehensive foundational data management, to non-intrusive systems that sit alongside existing architecture, providing different types of value to organisations at various stages of their data management journey.