Enhanced Analytics in AML Risk Manager
Prioritize money laundering alerts for enhanced risk management and operational efficiency
Organizations continue to face increasing risk associated with money laundering, with a regulatory environment that's focused on outcomes and alert volumes outpacing resource expansion. To more effectively manage these risks, institutions need technology that leverages their data assets to drive better insights into risk.
Enhanced analytics in AML Risk Manager from Fiserv combines behavioral analytics and rules-based alerts with supervised machine learning to optimize outcomes.
In combination with the AML Risk Manager alert investigation portal, analysts gain better access to the crucial information necessary for holistic analysis and accurate decision making required to remediate high-risk alerts and manage risk more effectively.
Enhanced analytics
in AML Risk Manager
- Evaluates alerts based on machine-learning models, informed by historical outcomes of investigations
- Accurately identifies alerts as productive or nonproductive
- Prioritizes and processes appropriately
- Evaluates alerts based on machine-learning models, informed by historical outcomes of investigations
Analytics capabilities in AML Risk Manager enable your organization to manage your money laundering risk in line with guidance from regulators globally and international organizations such as the Financial Action Task Force on money laundering.
Focused Accurate Detection and Alert Prioritization and Remediation
Enable analysts to focus on high-risk alerts
Reduce the number of false-positive alerts
Reduce operational costs by simplifying the alert process
Improve risk management with machine learning models built to support model risk governance requirements
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See how enhanced analytics in AML Risk Manager leverages behavioral analytics, machine learning and advanced modeling techniques to reduce false positives, so you can focus on higher risk alerts and manage risk more effectively.
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