Spectrum Data Science for AML
Reveal and analyze the patterns hidden in your data
With Spectrum Data Science for AML, you can spot suspicious connections between entities, accounts and transactions as they occur, based on anomalies in the data. It becomes easier to investigate where it matters, achieving greater efficiency and faster resolution.
Analytic segmentation is effective at identifying commonalities. Reverse that approach. Then you can instantly see what doesn’t belong and address it quickly. Integrated machine learning within a robust data hub makes your anomaly detection even smarter and faster over time.
Accelerate compliance and mitigate risk
Find connections faster
Use proven segmentation techniques to identify anomalous groupings of customers, agents, banks, transactions and more. Identify entities across disparate databases through
sophisticated data matching and analytics. Coalesce variations into a single entity by linking to the same address, account or other identifier.
Apply powerful technologies
Capture and evolve data models based on real-world complex relationships. Keep pace with fast-changing behaviors and uncover suspicious activities. Spectrum Data Science for AML
pairs robust data-science capabilities with its data hub and graph-database technology for highly efficient analysis.
Sharpen your insights
Create predictive models. Evaluate against previous cases and apply deterministic risk scores. Smart algorithms learn to differentiate between relevant and irrelevant data, instantly
uncovering anomalies to reveal hidden patterns and behaviors.
Transformative technology for AML:
• Fast, flexible graph database
• Intuitive, drag-and-drop interface
• Robust persistent data-hub repository
• Actionable analytics and machine learning
• Seamless integration with existing workflows and solutions