G-SIB Financial Data Issue Remediation, Standardization, and Governance


The client was a G-SIB facing considerable pressure from regulators, customers, and executive stakeholders to address a colossal data governance challenge resulting in more than six million manual adjustments to the bank’s transactional data per month. The bank was very active in international capital markets, trading in volume with every product and asset class through 100+ source systems. In addition to utilizing multiple platforms for the same product, numerous transformations were taking place as this source data flowed from origination to the general ledger, regulatory, and risk reporting systems.

This resulted in daily reconciliation issues, as the data flows were not standardized across platforms and thus very difficult to debug. Delv was selected to provide a current state analysis and future state target for managing the bank’s most challenging data governance issues.

Challenges and Solutions

Due to the urgency from stakeholders to provide relief from the manual issues as soon as possible, a wholesale reorganization and restructuring of the bank’s myriad data flows into a standardized enterprise model was not an option. The bank’s short-term directive was to help the CDO and IT team track, triage, and respond to the most urgent data issues in a way that eliminated redundant efforts and avoided creating new issues. Delv proposed the creation of a custom web-based issue tracker to collect data issues reported by business users. Custom database logic would then aggregate correlated issues and provide the basis for an effective IT response. Delv also enabled the integration of MIS feeds from the manual adjustment tool to allow effective prioritization of open data issues.

Before this could take place, a deep analysis of the data flows needed to be documented. This effort was critical to understanding precisely which transformations were happening to source data and why. When the analysis was complete, it would set the groundwork for the issue database schema and the process governing its usage.

Finally, it was known that several redundant static data bottlenecks were responsible for a sizable number of monthly manual adjustments. As part of its deep dive analysis of the data flows, Delv would identify the root cause of these issues and define requirements for fixing feeds or replacing static data sets with golden source repositories, and then collaborate with the CDO to ensure that all data flows were altered to reference this data.

Execution and Delivery

Delv business analysts tackled the data flow analysis immediately, patiently tracking through more than 100+ independent data schemas in the process. The static data bottlenecks were all identified, and unsurprisingly, were discovered to have shared considerable overlap with each other. The golden source repository schema was proposed and delivered to the CDO office for approval.

When each of the data flows was identified, Delv designed the UI and database schema for the issue tracker. Source systems and the ETL processes which governed their transformations were now linked to each other, ensuring data integrity as end users submitted issues. SQL queries and stored procedures were developed to generate reports which detailed where data bottlenecks were occurring, enabling the CDO to triage and troubleshoot issues more effectively.


Once the data issue tracker was implemented, the G-SIB saw a 60%+ reduction in the number of manual adjustments per month. The new data management methodology was working, as the CDO was now able to marshal and direct resources to fixing issues that had the most widespread impact first, further strengthening the case that the new approach to data governance applied by Delv was working. With the short term objective achieved, the G-SIB was confidently able to pursue the strategic vision of a standardized enterprise model solution for the firm’s data.

"Delv landed their team of business and systems analysts and hit the ground running. Their deep knowledge in regulatory reporting and ability to spec out data requirements is top notch."

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