AI-Powered Fraud Prevention at Dell Technologies

Discover how Dell Technologies uses LexisNexis® Emailage® Adaptive to improve fraud detection precision, reduce manual reviews and approve more legitimate ecommerce transactions.

Dell Technologies AI-Powered Fraud Prevention

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Reducing Ecommerce Fraud Without Increasing Customer Friction

Adaptive AI scoring supports faster, more precise fraud decisions

AI-powered fraud prevention
Dell Technologies was already operating a highly optimized fraud prevention strategy using multiple solutions and was not actively seeking to change its process. However, after seeing the performance gains enabled by LexisNexis® Emailage® Adaptive, the business recognised an opportunity to further reduce fraud risk and improve the experience for legitimate customers.

Dell Technologies wanted to gain more confidence with high-risk transactions, reduce friction, improve operational efficiency and enhance the customer experience. By deploying Emailage Adaptive®, the company increased the precision of its fraud detection strategy and improved operational agility.

Unlike traditional models, Emailage Adaptive is a fully AI-powered, self-calibrating solution that continuously adapts to localised fraud patterns based on customer-specific data. 

Since implementation, Dell Technologies has seen:

  • 2x more fraud captured in high-risk segments 
  • 1.7x more high-risk fraud attempts automatically declined 
  • 83% fewer low-risk transactions routed to manual review
  • Stronger revenue protection by increasing approval confidence on legitimate orders 

Emailage Adaptive has also helped Dell Technologies minimise reliance on static rules and manual policy adjustments. Its scoring now informs automated workflows, supports more confident decisions and helps allocate manual review resources more strategically.

Download the full case study to learn how Dell Technologies is improving fraud detection precision, reducing operational effort and creating smoother experiences for legitimate customers. 

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