Santander, a leading global financial institution with ~$1.9 trillion in assets and over 3,000 branches across Europe, proactively sought to modernize its rules-based AML systems, which generated unmanageable false positives and escalating compliance costs while limiting detection of financial crime. The transaction monitoring team identified machine learning as essential for rapid enhancements and a unified global framework. ThetaRay’s advanced software delivered by implementing a risk-based ML approach that slashed false positives, boosted crime detection accuracy, optimized compliance efficiency, and enabled seamless international operations—driving transformative results.

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