Prevent fraud in real-time to reduce operational costs and increase customer trust

Preempt fraud with rule-based patterns and select ML algorithms for reliable fraud detection. Use anomaly detection and fraud prediction to respond to bad actors rapidly.
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Detecting Financial Fraud at Scale

Benefits and business value

Win customer trust

Ensure security for customers to build trust and loyalty

Move fast and prevent losses

Move from rules to machine learning to respond in time and reduce operational costs associated with fraud

Scale Flexibly

Cut through all the data complexities and implement fraud prevention at scale with the Lakehouse

Reference architecture

Data used

Additional assets

Case studies



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