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Case Study - dLocal
Combining identity intelligence, advanced risk detection, and merchant-specific fraud strategies, dLocal strengthens its defenses against evolving payment threats.
Banks obsess over fraud losses, but the bigger cost is the uncertainty that slows decisions, frustrates customers, and limits growth.
Every false positive influence who stays and who leaves, gradually eroding portfolio quality while fraudsters keep trying.
Whitepaper
Access our whitepaper to understand how identity intelligence changes fraud outcomes long before transactions occur.
Fraud steals revenue and warps machine learning models. Learn strategies to reduce the noise and keep your training data clean, reliable, and fraud-aware.
Case Study - Peer-to-Peer Marketplace
By evaluating email legitimacy at signup, this mobile-first marketplace improved platform safety without slowing down real users.
Next-generation fraud prevention relies on verified identity, risk scoring, and behavioral continuity to spot subtle signs of risk before an attack occurs. Identity history remains the hardest thing to fake—and the strongest signal of trust.
AI fueled by email activity is unlocking sharper fraud detection. Learn how dynamic signals outpace static defenses, reduce false positives, and scale protection in real time.