Uncover suspicious financial activity more efficiently than ever. Get a complete view of threats across your entire institution. And streamline your monitoring, review and investigation processes.
Better understand your overall exposure
Develop comprehensive, cross-channel customer risk profiles using entity link analysis to identify complex patterns of behavior and suspicious associations among customers, accounts or other entities.
Fight financial crime more effectively & efficiently
Monitor more transactions and risks in less time with a system that integrates anti-fraud and anti-money laundering processes, and can run multiple scenarios and risk factors simultaneously.
Reduce false positives by up to 76%
Only SAS uses predictive alert analytics to significantly reduce false positives by automating decisions and scoring risk to more accurately identify the greatest threats before beginning an investigation.
Foster collaboration among fraud & AML teams
Centralized case management, a common repository for cross-channel data and shared workflow tools facilitate information sharing while reducing administrative costs.
- SAS® Anti-Money LaunderingTake a risk-based approach to monitoring transactions for money laundering and terrorist financing activities.
- SAS® Customer Due DiligenceRate new customers and update existing customer scores based on key events and new information.
- SAS® Detection and Investigation for BankingFind and stop organized and first-party application and payments fraud with a single, end-to-end solution.
- SAS® Fraud ManagementDetect, prevent and manage fraud enterprisewide in real time – from a single platform.
A common analytics platform and module-based solutions for enterprise fraud, customer due diligence, anti-money laundering and enterprise case management.
A hybrid analytic approach
Uses multiple analytic techniques for greater accuracy and better predictive performance.
Entity link analysis
Uncovers associative behavior or common ownership across related parties.
Correspondent banking scenarios
Provides a financial-services-specific data model.
Peer group anomaly detection
Compares an entity’s behavior to its historical behavior, as well as the behavior of its peers.
Customer due diligence capabilities
Rates new customers and updates existing customer scores as needed.
Reduces the time needed for analyses from hours to just minutes using supercharged scenario tuning and what-if analysis.
Enterprise data management
An enterprise approach to data management and consolidation combines data integration, data quality and master data management in a unified environment.
Flexible alert management
Assembles alerts from multiple monitoring systems, associates them with common entities, and automatically prioritizes and routes suspicious cases using a customizable interface.
Centralized case management
Lets you create multiple automated workflows for different types of cases – fraud, money laundering, etc.
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