How do ML models identify suspicious activity better than traditional rules?
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ML analyzes behavior patterns across millions of transactions, spotting subtle anomalies humans would miss. It adapts as new fraud tactics emerge, reducing false positives and improving financial security.
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Instead of fixed rules, ML compares each action to normal behavior profiles. Sudden spending changes or unusual access patterns trigger alerts faster than manual review.
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