Online fraud is constantly evolving to bypass the established strategies for detecting it. While rules are effective for finding known fraud schemes, behavioral analytics and machine learning bring increased visibility to detect suspicious activity and prevent fraud in real time.
Machine learning uses behavioral analytics to prompt action when suspicious activity is observed. Paired with a dynamic and flexible rules system, it covers both known fraud schemes and never-before-seen threats.
Stop the latest ATM and POS attacks that evade legacy transaction risk monitoring systems. Comparing fraud histories to find common attack locations and periods, this analytical tool uncovers fraud hotspots where customers may have had their cards cloned.
Put your consumer behavioral analytics and risk data to work by laying authentication on top of your existing infrastructure. Or combine with Appgate’s authentication offering to deploy a complete Risk-Based Authentication solution.
Unify and simplify the investigation process. Transactional case management capabilities allow you to efficiently handle all information related to alerts and cases from within the solution. Providing thorough reporting and analytics to help you stop attacks before financial losses occur.
Learn how Transaction Monitoring helps you simplify your overall approach to fraud management while improving customer experience.
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Read a more detailed dive into how this Transaction Monitoring featured allows you to identify comprised credit cards before fraud occurs.
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Fraud is in a state of constant evolution and defensive tactics must evolve along with them. Our Fraud Beat provides insights into the current threat landscape, helping organizations understand which areas are most important when implementing a strong anti-fraud strategy.
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Our team is available to help answer questions, demo solutions and discuss pricing. Just let us know when you’re ready!