Real outcomes from real-world challenges

With fraud rules frozen in place, this national retailer needed a scoring layer that could deliver results without re-architecting workflows. Elephant’s adaptive scoring saved $2.3M in chargebacks and reduced reviews by 15%. No rules rewritten. No approvals lost.

This global marketplace used Elephant to calibrate their model scoring and trust tiers, unlocking a 19.4pp lift in approval rates without raising chargeback risk. The results were smarter approvals, sharper signal separation, and estimated savings of $120M annually.

One booking platform reduced false declines and manual reviews by plugging calibrated trust thresholds directly into their decision engine. ROC-AUC jumped to 0.87. Risky bookings were caught earlier without disrupting trusted travelers.

Faced with growing bot attacks and identity abuse, this global social platform turned to Elephant to isolate trust signals earlier in the funnel. The platform surfaced 40% of risky registrations missed by their native model and saw precision lift across regions and user types.

This ecommerce leader needed a way to lower friction for legitimate users while maintaining strict fraud controls. Adaptive trust signals reduced review volume and helped cut unnecessary friction without increasing risk.