Anti-Fraud Suite

Innovative, feature rich and modular Fraud Detection Solution for Digital Banking and Payments featuring behavioral profiling incl. behavioral biometrics, transaction risk analysis and threat detection in one machine learning based analytics engine.

Solution Overview

ThreatMarks’s next-generation fraud prevention solution called Anti-Fraud Suite (AFS) was created as an answer to the pains of the financial services industry, constantly facing various forms of cybercrime, fraud, and regulatory challenges. We have found that existing fraud detection systems cannot compete with the ever-changing fraud landscape and evolving techniques.

ThreatMark Anti-Fraud Suite is based on deep behavioral profiling and machine learning and provides 360° digital banking protection inside all online and mobile channels. 

Anti Fraud Suite – AFS

Layered Security Approach

The solution covers all layers of online fraud prevention defined by Gartner, offering complete protection from both cyber threats and fraud.

ThreatMark Anti-Fraud Suite combines three capabilities that have become an absolute necessity for today’s connected world:

  • A powerful machine learning-based engine that can analyze each payment operation or active transaction in real time.
  • An evidence-based cyber threat detection mechanism that can detect zero-day malware, phishing, bots and other attacks seamlessly, without using agents and disturbing users.
  • Unique behavioral profiling techniques, including passive behavioral biometrics, that can be used for risk-based strong customer authentication to verify digital identities, without adding friction to legitimate users and customers.

ThreatMark AFS is better because:

  • It works on all devices, across all channels, through one integrated analytical engine.
  • It is fully customizable to fit your business needs and policies.
  • It has a modular architecture, meaning that it can be used as a primary anti-fraud solution or as an addition to existing fraud management, effectively filling gaps in the fraud and cyber threat protection layers.