AppsFlyer Launches DeviceRank, a Mobile Device-Level Ad Fraud Prevention Technology

Sep 27, 2016

AppsFlyer, a provider of mobile attribution and marketing analytics, released new data forecasting that app marketers will lose $100 million in 2016 due to verified mobile app install and engagement advertising fraud. The study’s findings are based on the company’s new anti-fraud technology, called DeviceRank. The technology provides protection for mobile app advertisers by automatically “cleaning” fraudulent devices from marketers’ campaigns aimed at driving app installs and post-install activities.  

While the study found the U.S. to be the most targeted region by fraudsters, the countries with the highest rates of app install and engagement ad fraud, when factoring for mobile population, are: Germany, Australia, China, Canada, and the U.K., followed by the U.S., Russia, and France. The research shows that fraudsters attempt to target specific countries depending on the potential payout they can get from falsifying their location to commit fraud. Countries with the highest cost-per-install and cost-per-action payouts have a higher fraud rate, while regions with relatively low payouts - including Indonesia, India, Brazil, Vietnam, and Thailand have a lower fraud rate.

AppsFlyer’s DeviceRank technology works similarly to a Credit Score, identifying questionable behavior and offering enhanced protection. It leverages a proprietary big data-powered algorithm to build an anonymized, multidimensional rating of every mobile device. Each device is rated on a scale from C (fraudulent), through B, A, AA ,and AAA. Devices with a “C” rating are automatically excluded from AppsFlyer’s attributed installs and analytics. With more than 1.4 trillion mobile interactions cataloged in our internal database over the past five years, and 98% of all mobile devices across the globe already rated. Additionally, DeviceRank’s unique architecture and machine learning allow the database and algorithms grow, learn, and adapt as new mobile devices come online, new interactions are catalogued, and user engagement patterns evolve.