Automated Machine Learning (AutoML) is dramatically improving the effectiveness and the efficiency of anti-money laundering (AML) and fraud detection. DataRobot invites you to partake in a peer to peer dialogue discussing the impact autoML can have across the entire financial crimes detection and prevention process.
Hear from practitioners how autoML is being used in KYC, risk scoring, suspicious activity monitoring, and is improving the efficiency of financial investigations units by prioritizing alerts and safely reducing time spent chasing false positives. Ways of using both supervised and unsupervised learning separately and in combination will be discussed.
- An overview of successful financial crime detection applications leveraging DataRobot's autoML platform
- How to apply both supervised and unsupervised learning techniques in financial crime detection
- Opportunity to hear how other financial institutions are leveraging machine learning in financial crime prevention
Date & Location:
06:00 – Arrival
06:15 – Introduction
06:25 – ML trends within compliance
06:45 – Open discussion / Q&A
08:45 – Event concludes