The eyeDES® Streamlined Platform

Our proprietary eyeDES® platform has been developed for the detection of payment fraud and event risk scoring. eyeDES® runs multiple customized predictive models that we build for different types of organizations on their available data. Bespoke models are designed for organizations by our experienced Data Scientists to deliver high degree of precision and stability.

 

Use eyeDES® Platform with your models

You can also choose to use eyeDES® platform to deploy models developed by your organization or by third parties. Contact us today for details and for a quote!

 

The platform offers a real-time processing system that allows to detect fraudulent activity at the moment of purchase by deploying and running custom predictive models. We develop not one single model but multiple models to address different data segments and business channels within the organization.

 

Once developed, the predictive models bespoke to each organization, are deployed on the eyeDES® platform immediately to score transactions or events in milliseconds. Reasons are delivered in the same time. So, what takes usually weeks or months, with the eyeDES® platform is done in seconds. We have streamlined the process, made it easy and cost effective.

 

eyeDES® 4.0 release with built-in automatic model retrain

Starting with the new eyeDES® 4.0 release, the platform is equipped with built-in automatic model retrain. So, once our expert work in developing the initial customized predictive models for your business is finished, the model retrain will be done automatically by the platform, offering organizations full autonomy.

 

Organizations are able to access the eyeDES® dashboard and reporting tools to monitor the performance of payment and risk operations. The dashboard can be accessed via a web user interface providing visualization of charts and metrics that can be adapted to fit each organization’s specific needs.

 

How it all started

The eyeDES® modeling technology and platform were developed by Features Analytics team lead by Dr. Cristina Soviany. The principles of the underlying algorithms, statistical analysis and pattern detection technology behind eyeDES® have first benefited the medical field and patients. Those principles have been used to find patterns in highly complex ultrasound Radio Frequency backscattered 3D data for predicting the occurrence of cancer. Dr. Soviany and Features Analytics team is pursuing continued research and development efforts to further progress the machine learning technology and eyeDES® platform performance for detecting fraud and manage the risk across all levels of the payment industry: merchants, banks, acquirers processors and issuers.