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ThetaRay offering uses AI against financial cybercrime

By Newsdesk
Wed 24 Jul 2019
FYI, this story is more than a year old

AI-based big data analytics provider ThetaRay has announced Version 4.0 of the company's namesake advanced analytics platform.

The update includes capability upgrades to help global banks detect and prevent financial cybercrime. 

ThetaRay's IntuitiveAI solutions replicate the decision-making capabilities of human intuition to detect “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 Aite Group fraud and AML practice research director Julie Conroy.

“In the face of this rapidly escalating threat landscape, it is imperative for banks, fintechs, and merchants to leverage solutions such as ThetaRay's to help analyse their vast amounts of customer and transactional data to efficiently and effectively detect anomalies.

ThetaRay's machine learning algorithms that comprise IntuitiveAI were developed by two mathematicians.

They analyse 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 capabilities,” says ThetaRay CEO Mark Gazit.

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 delivers a holistic view of a bank's threat landscape.

The new release also provides an additional method for anomaly clustering, which 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.

This clustering method ensures that AML and fraud teams have the right approach to analyse anomalous events with the method most applicable to a particular use case.

The addition of pattern-based clustering also enhances the built-in transparency and explainability of ThetaRay's “white box” AI applications.

ThetaRay's enterprise services foundation has been enhanced with additional API capabilities to make it easier for DevOps teams to automate financial crime and related solutions. 

They also make ThetaRay's system even easier to deploy, seamlessly integrating into existing workflows and processes so that businesses can continue leveraging their investments in existing infrastructure.

ThetaRay 4.0 also advances the company's cloud strategy with HDFS support on Microsoft Azure.

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