Large Financial Services Firm
Financial Firm Achieves Metadata Management Success with Rocket DI
Industry
Finance
Company
A Large Financial Services Firm, the world’s largest custodian bank and asset servicing company, provides investment management and wealth management services to its customers all over the world. With offices in 35 countries, the firm holds $41.7 trillion under custody and/or administration and $2.2 trillion in assets under management.
Challenge
The firm is a Global Systemically Important Financial Institution (GSIFI) and as such, is highly regulated as part of the strategic global financial system. With over 2,000 applications from asset servicing to treasury services, understanding and defining the provenance of data is critical for the firm’s regulatory and line of business (LOB) oriented processes. Regulatory fines, as well as the costs associated with bad data, present financial pressure to improve data management. As compliance demands become more stringent, these risks are only increasing. With the responsibility of processing such large quantities of information every day, the cost of bad data is significant—especially considering the average company loses 12% of its revenue due to bad data.
Strictly governing this data with transparency into its entire lifecycle is a daunting task, especially for a large firm. Like most large firms, this one has grown via acquisition, leading to systems complexity and a need for greater integration across layers of technology. Over time, changes in products, technologies, and organizational needs created a buildup of entangled systems that made data provenance challenging. IT teams needed to follow data from point of production to aggregation to consumption, despite complex system interconnection.
On top of this, as employees and departments access and alter data in their own data stores, lineage becomes more challenging. This creates additional work to gain visibility into every version of a data set, leading to technical debt. The firm required a comprehensive approach that would illustrate the flow of data and accompanying technical data sources so that users could leverage this data for remediation, forensic review, and data reconnaissance purposes.
Results
- Visibility: By proactively applying superior technology, performance, and interoperability, new visibility emerged throughout over 1,500 systems and thousands of critical data elements across 15 disparate lines of business. With the ability to trace data from its origin to enduser, the firm unlocked new opportunities for metadata management success Crucially, the lineage program captured data while supporting regulatory requirements. For instance, the expiration of the London Interbank Offered Rate (LIBOR) required visibility into the corporate treasury data lake and risk and resilience environment. In addition to reviewing over 150 applications, IT managers would have to dissect the databases and data at rest for LIBOR rates. In one area alone, the firm was looking at 20,000 COBOL programs that needed to be assessed. The project could potentially take years.
- Time Savings: Thanks to Rocket DI and the governance team’s assembly line process, leveraging the established data lineage to save years, when compared to manually defining the location of LIBOR rates, was achievable. In the end, the LIBOR project only took 11 weeks, providing huge cost and time savings. With insight from the lineage maps, the firm worked with the Rocket team to prioritize which applications to address first. Within the Rocket DI dashboard, employees can see where data lives, when the application stopped using the LIBOR rate, and when it started using a new rate. This visibility helped sustain the transition and ensured the organization had a total understanding of its IT ecosystem, while establishing the data lineage team as the resource for impact analysis of any application.
- Enhanced Scanning Capabilities: The firm also enhanced their scanning capabilities to achieve an automated stitching rate of 87%, which represents a 30% increase since program inception. Automated stitching supplies the efficient connection of assets and data objects representing the same data source. This model also allows for the analysis of data flows through systems at rest and in motion, and the identification of user-defined technologies and the reduction of technical debt. The firm’s data lineage team overcame system complexity to efficiently gain comprehensive data lineage across thousands of CDEs. Now, the organization is equipped to access reliable and trustworthy data that drives better business outcomes.
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Want to learn more?
Data lineage is crucial to compliance, but beyond that, it’s essential to obtaining the datadriven insights our organization needs. We need to trust our data to make informed, strategic decisions, which means we need to be able to find it, understand it, and know it’s accurate. This project in partnership with Rocket has helped us establish that trust in our data.