SEON has launched an expanded suite of artificial intelligence (AI) tools to cut manual review times by up to 50% and help fraud and anti-money laundering (AML) teams act on risks faster.

New features include similarity ranking to link and prioritise users across shared devices, behaviours, IPs and contacts, colour-coded risk indicators, and an AML screening agent that filters false positives to keep investigations within the SEON ecosystem.

Developed with input from fraud and compliance teams worldwide, the update focuses on transparency rather than “black box” outputs.

SEON’s “see-through” AI shows analysts what triggered an alert, highlights key risk signals and lays out clear decision rationale.

Other additions include AI-generated investigation summaries, explainable AI scoring, and a natural-language rule and filter builder that converts plain-English instructions into complex detection logic.

According to SEON’s 2025 Digital Fraud Outlook, 76% of businesses are increasing AI investments to amplify analyst capabilities rather than replace human judgment.

SEON says its new tools reflect this trend by revealing the reasoning behind each AI-generated insight, building trust and enabling rapid response.

The company’s AI operates on more than 900 real-time first-party data signals, rather than static third-party sources, capturing behavioural and digital footprint data as it happens.

This dynamic foundation underpins accuracy and helps analysts adapt to evolving fraud patterns.

“Fraud teams don’t only need more data; they need better context. By capturing risk signals at the earliest customer touchpoints, our AI turns massive data volumes into clear, actionable intelligence.

Our first-party data approach gives analysts both accuracy and transparency for confident decision-making.”

said Tamas Kadar, Co-founder and CEO, SEON.

The firm had recently raised US$80 million in its Series C funding round to support its expansion plans in North America and other global markets.

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