Delivering Trusted Customer Data for Compliance, Reporting, and Growth
How a Major Global Bank Streamlined KYC and Reporting with Tamr’s AI-Native MDM
Challenges
- Fragmented customer data across multiple regional systems created inefficiencies
- Aggressive data improvement timeline slowed by poor data quality and hidden source-level issues
- Manual data cleanup processes were costly and unsustainable
- Traditional rules-based MDM approaches projected to take 2-3 years—unacceptable for urgent compliance needs
- Lack of transparency limited adoption and stakeholder trust
Outcomes
- Consolidated data from 5 primary systems to create a single trusted view of customers
- Reduced duplicates by ~60% within weeks, uncovering hidden data and process issues
- Expanded mastered attributes from 20—for baseline Know Your Customer (KYC) and regulatory needs—to 120 in under a year
- Improved compliance reporting and accelerated KYC processes
- Built transparency and trust with consumers through benchmarking against external sources and clear data lineage tracking
For the Americas division of this global financial services company, mastering customer data was not only a matter of efficiency, it was a regulatory imperative. Fragmented data across regions and business units slowed KYC processes and regulatory reporting, while traditional master data management (MDM) approaches were projected to take 2-3 years before delivering value.
The ability to deliver value quickly was critical for us. Our immediate need was twofold. One, our compliance work around Know Your Customer. The second one was regulatory reporting. As a financial institution, we are subject to fairly hefty reporting to different sets of regulators. So we really started with the attributes that were requested by those different use cases.
The company began its data mastering journey with a sharp focus: improving KYC and regulatory reporting. Starting with just 20 foundational attributes such as name, address, and industry code, the team prioritized what mattered most to compliance and risk stakeholders. Tamr’s probabilistic AI models consolidated multiple sources into a unified golden record, reducing duplicates by 60% and exposing underlying issues in the data landscape that had previously gone undetected.
By benchmarking internal data against trusted third-party sources, the bank accelerated both data quality improvements and regulatory confidence. In less than a year, the scope expanded from 20 attributes to over 120, enriched by external datasets to deliver a comprehensive customer view.
Transparency and adoption were central to success. Business consumers were engaged throughout the journey with reports comparing old vs. mastered data quality, ensuring confidence and buy-in.
When compliance leaders asked, ‘How can you prove this data is correct?’ we had the answer. Benchmarking against external sources was a game changer.
Rather than tackling an unwieldy MDM project, the company started small and scaled quickly. The first success in the Americas is now serving as a blueprint for global expansion, which is critical as the bank pursues a strategy to operate as one global institution rather than fragmented regional entities.
Today, mastered customer data powers compliance, risk management, and emerging AI-driven initiatives. With trusted data at the foundation, the bank is better equipped to accelerate growth, streamline regulatory processes, and deliver more value to its customers worldwide.
See for yourself
Get a free, no-obligation 30-minute demo of Tamr, and discover how our unique AI-native MDM solution can empower you to deliver data you can trust.