Reduce costs by improving the efficiency of AML transaction monitoring using Machine Learning. Compliance organizations within banks and other financial institutions rely on machine learning to improve AML compliance programs. Today, the systems that aim to detect potentially suspicious activity are commonly rule-based and suffer from ultra-high false positive rates. Automated machine learning provides a solution to address this challenge.
In this workshop, Data Scientist May Masoud will show how to use automated machine learning to reduce false positive rates. The results: improved efficiency of AML transaction monitoring and reduced costs.
Discover how Automated Machine Learning enables you to:
- Develop and refresh AML predictive models in a timely manner
- Deploy more accurate models with a click of a button
- Operationalise AML models by following a user-centric process
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