Case Study: Food Delivery Unicorn achieves $6M annual fraud savings and 300% detection uplift with DataVisor

Food Delivery Unicorn Uses DataVisor For Fraud-Free Global Expansion

Food Delivery Unicorn, a global online food ordering and delivery platform with 100M+ monthly users operating in 20+ countries, was losing millions to promotion abuse and sophisticated buyer–seller collusion as it scaled into new markets. Existing rule-based systems couldn’t detect unknown, region-specific attacks in real time, created customer friction, and couldn’t handle the massive data volumes the business needed to process. DataVisor was engaged to provide a modern, real-time fraud prevention solution (dVector) using unsupervised machine learning.

DataVisor deployed its dVector platform and unsupervised ML to detect bot-registered accounts at registration, uncover coordinated buyer–seller collusion, and support high QPS low-latency decisioning with rapid onboarding. The solution delivered a 300% detection uplift, caught 60% of fraudsters at registration, and saved the customer roughly $6M annually while reducing false positives and enabling frictionless growth.