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Data sheet

NetReveal Customer Due Diligence

03.29.2024
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NetReveal Customer Due Diligence (CDD) addresses the challenge of balancing risk assessment and customer experience by providing end-to-end customer risk profiling, seamless data integration, continuous monitoring, efficient alert management, dynamic risk dashboards, automated event triage, and adaptable UBO management, all enhanced through machine learning and AI for improved efficiency and faster risk detection.

Challenge: Navigating complex networks and ensuring customer experience while balancing risk assessment and resource allocation is vital to managing costs and maintaining a strong risk posture.

Solution – NetReveal Customer Due Diligence (CDD):

  • Customer Risk Profiling:
    • Provides end-to-end customer risk profiling using machine learning (ML) and AI.
    • Offers a single, comprehensive view of dynamic customer risk.
    • Utilizes key third-party and existing data for continuous monitoring throughout the customer lifecycle.
  • Seamless Data Integration:
    • Holistic risk assessment with frictionless onboarding.
    • Automates data enrichment and quick understanding of complex corporate structures.
  • Continuous Monitoring:
    • Adjusts risk scores based on behavior changes and triggers automated alerts for suspicious activities.
    • Facilitates prompt interventions.
  • Alert Management:
    • Prioritizes higher-risk alerts to focus on critical decisions.
    • Maintains a single active alert per customer to minimize alert volumes.
  • Dynamic Risk Dashboard:
    • Visual representation of the customer’s risk profile for faster, informed decisions.
  • Event Triage:
    • Automates the first line of triage by scoring alerts based on priority.
  • UBO Management:
    • Captures and scores Ultimate Beneficial Owners (UBOs) data, both manually and via third-party integrations.
    • Adapts UBO threshold based on business processes or regulatory mandates.

Key Benefits:

  • Reduction in alert volumes.
  • Faster risk detection.
  • Enhanced operational efficiency.
  • Integration with supervised and unsupervised machine learning for improved behavioral risk scoring.
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