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SEON unveils an explainable AI platform processing real-time data signals for fraud teams with AML screening agent prioritization: reduces manual fraud review time by 50% with similarity ranking, color-coded risk signals and natural language rule builder

September 30, 2025 //  by Finnovate

SEON, the command center for real-time fraud prevention and AML compliance, has launched a comprehensive AI suite that cuts manual review time by up to 50%. The platform now automatically detects linked users, highlights critical risk signals with color-coded indicators and includes an intelligent AML screening agent, keeping teams within the SEON ecosystem for seamless data-to-action workflows. Rather than operating as a black box, SEON’s see-through AI shows analysts exactly what happened and why it matters. Built with input from fraud and compliance teams worldwide, the tools turn SEON’s comprehensive data foundation into clear next steps without requiring analysts to jump between multiple solutions. SEON’s new capabilities address every stage of fraud and AML investigations, turning complex data relationships into clear next steps. The AI suite includes: Risk Signals: Color-coded indicators surface high, medium and low-risk activity across email, phone, device, OS and IP data so analysts can spot the most critical triggers at a glance. Similarity Ranking: Links and ranks connected users through shared devices, behaviors, IPs and contacts, letting analysts skip manual graph-building and focus on top priorities. AI Investigation Summaries: Generates clear, bullet-point explanations of each alert and transaction, turning complex digital fingerprints into concise narratives that explain why activity was flagged. Explainable AI Scoring: Complete visibility into what drives the risk score, including individual signal contributions, supporting both analyst confidence and regulatory requirements. Natural Language Rule & Filter Builder: Analysts describe detection logic in plain English, and AI automatically generates complex rules and filters. Teams adapt to new fraud patterns without technical coding knowledge. AML Screening Agent: Identifies false positives from screening hits, providing AI-backed prioritization so analysts focus on alerts that truly matter.

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Category: Cybersecurity, Innovation Topics

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