Applied Machine Learning in Finance & Detecting Money Laundering скачать в хорошем качестве

Applied Machine Learning in Finance & Detecting Money Laundering

In this talk, Vahan discusses recent trends in machine learning and what they might mean. He frames the discussion with a case study on using ML for search engine marketing optimization for Capital One, pitting traditional manual optimization practices against an algorithmic approach. Bio: Vahan DerKaloussian is a senior manager of data science, leading the statistics and modeling team at Capital One Canada. He is responsible for the overall modeling ecosystem, including model build/maintenance/monitoring, experimental design, and statistical consulting. He holds a degree in Actuarial Science from the University of Waterloo.   / vahan-der-kaloussian-b6024b54   Detecting Money Laundering In this talk, Ashrith will be introducing you to the idea of using machine learning for detecting money laundering. The idea behind using ML for detecting money laundering is that the current rules-based engine have limited visibility into money movement. And as models learn the nuances of money movement, especially illegal, much better money laundering detection is possible. Bio: Ashrith Barthur is a Security Scientist at H2O currently working on algorithms that detect anomalous behaviour in user activities, network traffic, attacks, financial fraud and global money movement. He has a PhD from Purdue University in the field of information security, specialized in Anomalous behaviour in DNS protocol.   / abarthur   Ashrith's slides are here: https://www.slideshare.net/0xdata/ant...