DataVisor Launches Feature Platform To Automate Fraud Detection

DataVisor has announced the launch of its new Feature Platform, which automates fraud detection through the use of artificial intelligence and machine learning data capabilities.

As the leading fraud detection platform powered by transformational AI technology, DataVisor uses proprietary unsupervised machine learning algorithms so that organizations can detect fast-evolving fraud patterns, as well as prevent future attacks.

With the release of its new Feature Platform, organizations will now have access to automated feature engineering across multiple data sources that can build features in minutes. In addition, the platform can recommend available features for specific use cases, such as transaction fraud, and supports advanced features created through deep learning technologies.

Teams can engineer any features with just a few clicks or via simple coding, without the need for additional support from IT departments. The features are built in a centralized platform, allowing re-use and easy maintenance so that multiple teams can share features for various business tasks.

And with the DataVisor Feature Platform integrating with its Global Intelligence Network (GIN), feature derivation and model performance are further improved. In fact, the DataVisor GIN is powered by derived signals from more than 4.2 billion protected accounts and more than 800 billion events across industries, which significantly boosts machine learning.

“The hallmark of the DataVisor approach is our holistic approach to data analysis using sophisticated feature engineering and machine learning. The Feature Platform incorporates this ethos and delivers organizations with proven means to develop effective machine learning models more easily and faster, and hence stop fraud loss from occurring,” DataVisor CEO Yinglian Xie said in an emailed press release.