Case Study
A Tier 1 investment bank faced fragmented client data across multiple systems, resulting in €50M in regulatory fines and delayed onboarding that cost $100M+ annually in lost trading revenue.
DataCatalyst implemented an industry-specific MDM platform supported by NLP capabilities and graph databases to create golden client records, delivering a unified source of truth for client data.
Client onboarding accelerated from 14 days to 48 hours, recapturing $75M in annual revenue, achieving 100% MiFID II compliance, and reducing false-positive AML alerts by 30%.
A Tier 1 investment bank operating in global capital markets was struggling with severely fragmented client data spread across multiple systems, including KYC (Know Your Customer), CRM, Onboarding, AML (Anti-Money Laundering), and risk management platforms.
This fragmentation created a chaotic data environment that lacked consistency and reliability. The bank’s Head of Customer Data, caught between business demands and technology limitations, could see that these data issues were causing serious operational and regulatory problems across the organization.
The disjointed nature of client information had already resulted in substantial regulatory penalties, including €50M in MiFID II fines and US MRIAs. Without a unified view of their clients, the bank was unable to effectively demonstrate compliance with increasingly stringent financial regulations.
The bank urgently needed to address several critical issues stemming from their fragmented client data:
Previous internal attempts to address these issues through manual reconciliation, workflow adjustments, and point solutions for specific regulations had failed to solve the fundamental data problems. As regulatory fines mounted and revenue losses continued, the bank recognized the need for specialized expertise in enterprise data management.
DataCatalyst deployed a lean team of seasoned experts to work closely with the bank, following our proprietary Accelerate methodology that emphasizes business-driven requirements and iterative value delivery. Our approach began with a thorough analysis of the current data architecture and processes.
Rather than proposing an unwieldy solution that would take years to implement, our team worked collaboratively with stakeholders from both business and IT departments to design a targeted approach focused on delivering rapid, measurable value. We prioritized a Minimum Viable Product (MVP) implementation that addressed the most critical pain points first, with a clear roadmap for future enhancements.
Our business-driven approach ensured that requirements were directly tied to the bank’s strategic objectives and operational needs, rather than being defined by technology constraints. This alignment was crucial for ensuring user adoption and realizing business value.
DataCatalyst designed and implemented a comprehensive solution leveraging industry-leading technologies and our deep financial services expertise:
Our lean, purpose-built team of data experts combined management consulting acumen with deep technical knowledge to deliver this solution efficiently and effectively. Unlike larger firms that might deploy dozens of less experienced consultants, our “gray-haired SWAT team” approach meant that every team member brought valuable expertise to the project, ensuring faster delivery and superior results.
Implementing this transformative solution required significant changes in how the bank approached data management:
Through an approach that emphasizes clear communication, thorough documentation, and business-driven priorities, our experienced team anticipated challenges and proactively addressed them. This ensured a smooth transition with minimal disruption to ongoing operations.
The implementation delivered remarkable, measurable results within a compressed timeframe:
These results demonstrate the power of DataCatalyst’s approach: focusing on business value, deploying lean teams of experienced experts, and using our Accelerate methodology to deliver tangible outcomes quickly and efficiently.
This successful data transformation has positioned the bank for long-term success and competitive advantage:
The project continues to deliver value as the bank evolves its data strategy and capabilities to thrive in an increasingly dynamic business environment.