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Learn more about how DataVisor uses unsupervised machine learning to reduce false positives and false negatives.
1. Reduce costly investigations driven by false alerts, allowing you to focus on investigating truly suspicious accounts.
2. Spend less time managing rules with global linkage view of bad actors and automatic rule generation powered by unsupervised machine learning.
3. Detect known and unknown threats for all product types, geographies and people by looking at all events for all accounts.
"90 percent to 95 percent of all alerts generated by AML alert engines are false positives."