Case Study: Momo prevents mass-registration fraud and preserves user experience with DataVisor

DataVisor Helps Momo Users Find Friends Not Threats

Momo is a mobile-based social networking app with over 180 million users that helps people chat and meet nearby. Despite SMS authentication, Momo was targeted by organized fraudsters who created thousands of fake or compromised accounts (using device flashing and GPS simulation) to run spam, phishing and illicit-commerce campaigns that exploited Momo’s location features. To combat this, Momo engaged DataVisor and its Unsupervised Machine Learning (UML) Engine and Global Intelligence Network (GIN).

DataVisor deployed its UML engine (fed by the GIN) to analyze all accounts and events simultaneously, identify suspicious clusters and surface “sleeper cell” accounts during incubation. By providing early detection, real-time scoring and full campaign visibility, DataVisor enabled Momo to eliminate fraudulent accounts before they launched attacks, producing a dramatic reduction in spam, phishing, illegal commerce, prostitution ads and account hijacking and helping sustain Momo’s rapid user growth.

Momo

Yan Tang

Chief Executive Officer