Meetup: Detecting Money Laundering Networks Using Machine Learning

This video was recorded in Mountain View on October 3, 2019. Description: How do you solve Anti-Money Laundering using Driverless AI? In this presentation, we will see how to reduce false-positive alerts, which is a big problem for financial institutions. Using this approach you can quickly and easily design models that will reduce false-positive alerts significantly while keeping the false-negative number low. Speaker's Bio: Ashrith is the security scientist designing anomalous detection algorithms at H2O.ai. He recently graduated from the Center of Education and Research in Information Assurance and Security (CERIAS) at Purdue University with a Ph.D. in Information security. He is specialized in anomaly detection on networks under the guidance of Dr. William S. Cleveland. He tries to break into anything that has an operating system, sometimes into things that don’t. He has been christened as “The Only Human Network Packet Sniffer” by his advisors. When he is not working he swims and bikes long distances.