Reduce AML False Positives Before They Slow Down Your Team

AML false positives can account for over 90% of alerts, creating noise that wastes analyst time and delays real investigations. SEON uses AI to flag likely false positives, highlight mismatches or weak associations, and help teams focus on genuine risk.

  • Flag likely false positives automatically with AI
  • See explanations and confidence scores for every flagged hit
  • Keep analysts in control of the final decision

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  • See the full picture instantly with AI summaries and risk signals
  • Understand what signals are driving the AI insights score
  • Expose connected users to uncover fraud rings
  • Reduce time reviewing flagged hits with the AML screening agent

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With over 350 reviews, SEON is the market leader and G2’s best fraud prevention platform.

Discover How Companies Win

“It is a flexible tool that helps us track possible money laundering activity with features that are highly customisable and help a lot with automation. The high number of sources that the feature has allows analysts to consider their decisions from different perspectives. This allows the relevant teams to further their knowledge of the customers and for the company to stay compliant.”

Márton Hajagos

“It is a robust analytics and risk management system that offers customizable options for setting relevance thresholds and reducing false positives. This system seems particularly useful for compliance purposes, allowing the team to monitor customer behavior, background, and appearances on lists for various reasons.”

Monika Zaja

Frequently Asked Questions

How does SEON help reduce AML false positives?

SEON’s AML Screening Agent uses AI to evaluate customer screening hits in real time. It cross-validates each hit against the input data, highlights mismatches or weak associations, and flags likely false positives for analyst review.

What does the AI actually look for when flagging false positives?

The AI is trained to spot discrepancies such as different company names, different company types, wrong jurisdictions, country mismatches, date-of-birth differences, first- or last-name mismatches, outdated sanctions information, and other weak associations that suggest the result is not a genuine match.

Does SEON automatically dismiss false positives?

No. SEON flags likely false positives and provides supporting context, but analysts remain in control of the final decision. Users can review the explanation, check the confidence score, and then decide whether to mark the result as a false positive.

What does SEON show for each flagged hit?

Each flagged hit includes a short explanation of the discrepancy and a confidence score that indicates how confident the AI is that the hit is a false positive. The interface also visually marks flagged hits so analysts can review them faster.

How does SEON help analysts review alerts faster?

By identifying likely irrelevant matches within milliseconds and surfacing the reason why they may be false positives, SEON reduces the time analysts spend manually comparing hits and lets them focus on higher-risk alerts first.