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Using new AI tools to improve anti-money laundering and drive efficiency
The panel
- Michael Barrett, Senior Director, Product Management, AML, NICE Actimize
- Andrew Fleming, Global Compliance MI Senior Risk Reporting Manager, HSBC
- Richard Snookes, Chief Compliance Officer, Sberbank CIB
- Moderator: Tom Osborn, Editor, Risk Management, Risk.net
Today’s evolving regulatory environment and criminal typologies require anti-money laundering (AML) compliance teams to adopt technologies such as artificial intelligence (AI) and machine learning to improve detection and analyst workflows.
This webinar explores how the marriage of AI and expert models lays the groundwork for a strong AML programme foundation that eliminates backlogs and creates efficiencies.
Key topics discussed:
- Leveraging collective intelligence from an industry-wide view
- An impact analysis of new policies and rule changes on client profiles
- How machine learning-based segmentation increases the quality of alerts
- Increasing tuning frequencies without cumbersome data migration projects
- How automatic alert triage processes reduce alert volume
- Hibernating alerts until customer activity increases the risk.
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Copyright Infopro Digital Limited. All rights reserved.
You may share this content using our article tools. Copying this content is for the sole use of the Authorised User (named subscriber), as outlined in our terms and conditions - https://www.infopro-insight.com/terms-conditions/insight-subscriptions/
If you would like to purchase additional rights please email info@risk.net