Case Study: United Overseas Bank achieves personalized recommendations for millions and accelerated AML detection with Cloudera

United Overseas Bank personalizing recommendations to millions and improving anti-money laundering detection

United Overseas Bank (UOB), a leading full-service bank in Asia with over 500 offices across 19 markets, set up Singapore’s first centralized Big Data Analytics Centre to deliver frictionless, personalized banking and stronger AML controls. The bank faced the challenge of consolidating data from dozens of separate systems—including unstructured voice and text—because legacy databases constrained the volume and variety of data needed for effective customer analytics, recommendation engines, and transaction monitoring.

Using a Cloudera modern data platform (supporting ~2 PB and thousands of daily file ingests) and Cloudera Machine Learning, UOB enabled self-service analytics and faster AI/ML model delivery across business units. The solution powered personalized recommendation engines (1M+ personalized recommendations and higher conversion rates), enhanced AML detection—cutting time to identify new links from three months to three weeks—and saved relationship managers over 1,000 hours, while supporting sentiment analysis and broader customer‑insight initiatives.

United Overseas Bank

Richard Lowe

Chief Data Officer