Revelock

What do you like best?

BugFraud is an expert solution to prevent online banking fraud as detect all fraud use cases, including unknown malware. It creates a unique profile for each user by gathering thousands of parameters relating to their behavioral biometric, environmental and device information. The solution uses deep learning to analyze anomalies and to detect fraudulent threats involving identity theft or customer manipulation across the entire banking session, and therefore detecting malware on the device. The way we have integrated the product is transparent for the users and enhance their customer experience. Information is available via API and a web management console to receive alerts and risk score per session in real time. The GUI has a lot of information about the sessions and all the alerts that it'd had. Buguroo is continuously evolving and releasing improvements that make the product and the detection of anomalies and fraudster behaviors more accurate and better.

What do you dislike?

The product needs to be fine-tuned and customized for our needs before it reaches its higher fraud detection rate and lower F/P Ratio. Also the retention period should be increased, thus it has lead to some late detection, as alerts can only be consulted via GUI.

What problems are you solving with the product? What benefits have you realized?

We use the alerts to improve the rules including the biometric user profile, and the environment. It permits us to detect delicate users who could be victims of fraud. Furthermore, with the use of Fraudster Hunter, we've found devices and users related with a case of fraud which our controls hadn't detected.