Case Study: Fraud.net (customer) achieves 99% human verification and 40% more accurate applicant risk detection with Fraud.net’s Application AI™ (solution provider)

Fraud.net - Customer Case Study

Fraud.net needed to assess application risk in real time across mobile apps and web portals to verify legitimate customers and stop duplicate and fake accounts, synthetic identities, and bots from opening accounts, applying for loans or cards, or onboarding as merchants. To address this, Fraud.net used its own Application AI™ product to deliver fast, explainable applicant risk scores and reduce friction for legitimate users.

Fraud.net implemented Application AI™ using collective intelligence, device fingerprinting, custom ML models, and a third‑party data marketplace, exposing fully explainable risk scores via API plus a customizable case management and analytics portal. The solution went live in under 30 days, returns scores in under 300 ms, preserves a frictionless experience for 99+% of trusted customers, helped a gaming app verify 99+% human registrations, and enabled a micro lender to improve risky applicant isolation by 40%.

Fraud.net

Marketing Team