DataVisor's Yuhao Zheng and Boduo Li share advanced techniques for managing thousands of spark workers to analyze billions of events at a time, including clustering workers and automated, optimized management of DataVisor's spark infrastructure.
DataVisor's Ting-Fang Yen and Arthur Meng present a novel deep learning technique for scalable online fraud detection among billions of users.
Does the fact that UML doesn’t require labels mean that there is no benefit at all to labels? If label data exists already, how can it be used to improve UML detection results? In this article we discuss how labels can be effectively used in UML detection, even if they are not required.
Introduction There are many technical articles that describe supervised and unsupervised machine learning methods. In this guide, we will explain a few high level differences when it comes to choosing between the two. Comparison 1: [...]
The DataVisor Online Fraud Report took a look at our base of more than one billion users across 172+ countries in the world. Using this massive amount of data, we were able to identify some of the favorite tools and attack techniques that online criminals from around the globe favor when doing their dirty work.
As mentioned in my previous articles, traditional rule-based transaction monitoring systems (TMS) have architectural limitations which make them prone to false positives and false negatives: Naive rules create a plague of false positives that are [...]
False positives have a terrible reputation among anti-money laundering (AML) circles. As mentioned in my previous article on ending the false positive alerts plague, approximately 90-95 percent of alerts generated by Transaction Monitoring Systems (TMS) [...]
Keith Furst is the Founder of Data Derivatives, and has years of experience within a variety of financial institutions including Tier One wholesale banks, investment banks, foreign bank branches, commercial banks, retail banks, broker-dealers, prepaid [...]
Wondering if your company has any crime rings sleeping among your users? Most will acknowledge that there are likely some accounts lurking here or there, but may not realize that it’s a big problem.