WEBINAR: Enhancing Anti-Money Laundering (AML) Programs with Automated Machine Learning - 11 January 2018

Enabling the AI-Driven Enterprise

Thursday, January 11, 2018  6:00 PM. 45 minutes with Q&A

Compliance organisations within banks and other financial institutions are turning to machine learning for improving their 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 webinar, Justin Dickerson, General Manager of Global Finance for DataRobot, and Dan Yelle, a Customer-Facing Data Scientist for DataRobot will show how automated machine learning can be used to reduce false positive rates, thereby improving the efficiency of AML transaction monitoring and reducing costs.

You’ll discover how Automated Machine Learning provides:

• The ability to develop and refresh AML predictive models at any time
• The ability to deploy models with a click of a button
• The ability to operationalize AML models by following a process that is user-centric

Speakers

Dan Yelle

Customer-Facing Data Scientist, DataRobot

Justin Dickerson, PhD

General Manager of Global Finance, DataRobot

Register here