ACCELERATING DATA CATALOGING AND GOVERNANCE WITH GENAI

Client Background

The client, a diversified financial services firm, acquired a market-making operation in 2022 to expand its fixed income and institutional trading capabilities. Now, as part of its data management strategy, the firm is integrating this new data with its existing Fixed Income Capital Markets business into a centralized data catalog. This effort supports analytics, risk management, and regulatory compliance for its $100 billion LFI readiness initiative.

Challenge:

The client faced significant challenges in managing metadata across an expanding and complex system landscape. Manual onboarding of metadata was slow and inconsistent, requiring extensive effort to align technical and business data elements. Regulatory demands from G-SIB requirements added urgency, while recent acquisitions introduced fragmented, siloed data sources. Limited SME availability further strained resources, hindering progress on strategic initiatives.

Solutions Implemented: Element22’s AI-Enabled Data Catalog Acceleration Framework

Element22 delivered a solution that unbundled the metadata onboarding process, intelligently assigning tasks between Generative AI and human SMEs, and then rebundled the results to dramatically accelerate delivery while improving quality.

Key features of the solution included:

• Generative AI Integration: Leveraged OpenAI API and Microsoft Co-Pilot to automate metadata discovery, generate definitions, and assist with classification.

• Smart Classification Engine: Mapped TDEs to logical BDEs and standardized business terms for clarity and consistency across the firm.

• Domain & Responsibility Framework: Established domains, classes, and data ownership structures to align with the firm’s governance model.

• Compliance Alignment: Designed to meet G-SIB data management and reporting standards, ensuring regulatory readiness.

• Scalable Architecture: Built to handle data ingestion from newly acquired systems and existing infrastructure seamlessly.

Outcomes & Benefits Delivered:

• Drastic Time Reduction
  Reduced metadata onboarding from weeks or months to days or hours.

• Enhanced Metadata Quality
  Delivered highly accurate and consistent data definitions, often outperforming manual SME efforts.

• Increased Efficiency
  Freed SMEs from repetitive tasks, enabling focus on higher-value strategic initiatives.

• Improved Data Governance
  Created a centralized, standardized data catalog to support compliance, reporting, and decision-making.

• Scalable & Future-Proof
  Enabled rapid onboarding of metadata from future acquisitions and system changes.

Conclusion:

Element22 designed and implemented an AI-accelerated metadata onboarding solution tailored to the client’s regulatory and operational needs. By leveraging GenAI and a structured framework, the firm significantly reduced processing times, improved metadata accuracy, and established a scalable foundation for data governance. This empowered the organization to meet tight regulatory deadlines, integrate complex data landscapes, and shift SME focus to strategic, high-value initiatives.