Our client, an international financial services firm, had little history of enabling Line-of-Business capabilities across the enterprise. They struggled with a fragmented, redundant view of data resulting from a lack of effective metadata management and data traceability and lineage challenges.
Additionally, they had few data standards, definitions, or policies in place, rarely reused common data, and followed minimal proactive data quality improvement practices. The lack of clear roles and responsibilities exacerbated these issues.
With key regulatory challenges approaching, including all key risks (BCBS 239), intraday liquidity (BCBS 248), and KYC/AML, our client engaged Knowledgent to establish a data governance function and operating model with supporting active data quality management stewardship. This included developing a shared service charter, maturity framework, and enterprise operating model.
As part of the approach, our team implemented a data intake management process, which defined roles and responsibilities to ensure ownership over all procedures. We also identified the technology assets that could be leveraged to define a data management architecture framework, including service offerings, architecture recommendations, key control points, and metrics.
To test the new model, we executed an operational pilot to accelerate the formation of the new organization and to begin performing key operational capabilities, such as data discovery and data profiling.
At the end of the project, our client had formed a new enterprise data governance and management organization that effectively integrated with the broader organization (including reporting to the Board of Directors).
They also had defined the services and operating model the organization will utilize going forward. Following the detailed roadmap, delivered by our team, allows our client to support both an initial operational set of services and capabilities and a services and technology maturity model to achieve the full vision.
As a result, our client was able to establish a operational data management framework aligned with the new established architecture and enterprise data environment to oversee acquisition, management, and destruction of data.