Fraudulent devices were detected using AppsFlyer’s DeviceRankTM technology,

the industry's first fraud prevention solution to identify and exclude fraud at

the device level (unlike the current IP or app-level solutions). DeviceRankTM

leverages a proprietary big data-powered algorithm to build an anonymized,

multidimensional rating of every mobile device. Ratings are built from over

a dozen points of metadata, including device details, engagement history,

historical fraud modeling scoring, IP address and geolocation, transactional

data, verified transaction data and more. DeviceRankTM has already rated 98% of

all mobile devices across the globe.

Learn more at www.DeviceRank.me

With the explosion of mobile usage, advertisers have dramatically increased their mobile

ad spend. And with money pouring in, fraudsters have followed suit. But the data on

mobile ad fraud is still scarce. The IAB estimated that it cost advertisers $1.3 billion

worldwide, but this number is centered on analyzing fraudulent and invalid traffic driven by

brand marketing with little focus on performance app marketing.

As mobile app install spend is significantly rising, the impact of fraud on this growing

segment of mobile advertising has not been properly documented. Until now.

In this industry-first report, we have mapped out the scope of mobile app install and post-

install app engagement fraud, including a breakdown by country, operating system and

OS version. The data is based on AppsFlyer’s DeviceRankTM technology, which accurately

detects fraudulent devices (read more on DeviceRankTM below).

Mobile app install and engagement fraud will cost advertisers across the globe up to $350 million in 2016. This figure is based on the DeviceRank algorithm, which separates between verified fraud ($100M in loss) and suspected fraud ($250M in loss) depending on the number of signalsit receives.

This forecast accounts for scenarios such as mis-attribution due to fraudulent click data, paid installs from fraudulent devices, fraudulent and simulated in-app events and the impact of fraudulent data on lookalike targeting and retargeting. Forecast data is based on normalized ad spend and install trends from January 2015to September 1, 2016.

in 2016

$100 MILLION

$250 MILLION

VERIFIED FRAUD

SUSPECTED FRAUD

$350 MILLION

Learn more at: www.DeviceRank.me