Fraud prevention and anti-money laundering are tough use cases to tackle. They become even more difficult when data originates from various sources, not complete or correct, or even if it’s not kept up-to-date.
To make this work, machine learning models need the data in the right format, but data quality processes at Hadoop cluster scale are no picnic – and the moment that models gets put into practice, the data will be out of date. So, you’ll need a way to keep the cluster in sync with transactional source systems in real-time – which shouldn’t be too hard, right?
Register now for this July 19th webinar to explore solutions for using Hadoop, data quality and change data capture to deliver AML solutions at scale
|Thu Jul 19 @17:00 - 06:00PM|
Real-Time CDC and Data Quality at Scale Washes Out Money Laundering
|Wed Jul 25 @17:00 - 05:30PM|
Webinar: Which Change Data Capture Strategy is right for you
“If you talk Data to business, it goes to their head. If you talk to business about empowering and enabling them to make informed business decisions based on accurate and trustworthy data that will give them the competitive advantage, it[…]Read more...