Anomaly & pattern detection

Surface anomalies and risky patterns in event data.

What it is

Fraudulent refunds, discount abuse and coordinated buying behavior hide inside millions of routine transactions. Linkube runs statistical and ML detectors over the event stream — pseudonymized identifiers, anonymized demographic and technical attributes, no direct PII — and flags the sessions and accounts that deviate from established baselines. Risk and loss-prevention teams get ranked alerts with the evidence attached, so investigators start from the strongest cases instead of raw logs.

What you get

  • Ranked alerts instead of undifferentiated exception reports
  • Detects slow-building patterns single-event rules miss
  • Baselines that adapt as behavior shifts
  • Privacy-by-design: pseudonymized identifiers, no direct PII

How it works

  1. 01

    Stream pseudonymized transaction, return and account events into the risk layer

  2. 02

    Score each event against behavioral baselines and known abuse patterns

  3. 03

    Send prioritized alerts to investigator queues and measure confirmed-case rates

Works well with

Ready to see Linkube on your data?

Book a working session with our team and we’ll map Linkube to your planning and risk workflows.

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