AI-based Big Data analytics vendor ThetaRay releases Version 4.0 of the company’s namesake advanced analytics platform. The updated platform is the first to offer hybrid learning and adds pattern clustering, DevOps Tools and enhanced cloud capabilities.
In particular, ThetaRay 4.0 with IntuitiveAI gives banks a powerful new weapon against financial cybercrime.
And ThetaRay says its solutions replicate the powerful decision-making capabilities of human intuition. This means it detects “unknown unknowns” that cannot be identified by first-generation AI or legacy products.
“Fraud and money-laundering schemes continue to grow in both volume and sophistication,” says Julie Conroy, Research Director, Aite Group.
ThetaRay’s machine learning algorithms that comprise IntuitiveAI were developed by two world-renowned mathematicians. They analyse massive amounts of data and discover relationships between seemingly unrelated events.
They enable banks to pinpoint activity that suggests money laundering, terrorist financing, human and drug trafficking, and other financial crimes.
“We are pleased to introduce these robust capabilities,” says ThetaRay CEO Mark Gazit. “Our award-winning IntuitiveAI is more powerful than ever and able to detect even the most sophisticated and dangerous unknown threats. ThetaRay 4.0 reconfirms our commitment to provide next-generation financial crime prevention solutions that exceed the requirements of customers and partners.”
ThetaRay 4.0: a new hybrid learning approach
Version 4.0 provides a new hybrid learning approach. The hybrid supervised/unsupervised learning capability integrates the two learning styles and applies the most effective one based on use case. This approach finds significantly more potential threats through a single process. And says ThetaRay, it delivers a holistic view of a bank’s threat landscape.
The new release also provides an additional method for anomaly clustering. This is a critical enabler to accurately detect more true positives while dramatically decreasing the number of false positive alerts. In version 4.0, customers can now cluster identified anomalies by pattern, in addition to a density-clustering approach.