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4 min read

Programmatic 101: Deep-dive into mobile ad fraud

Jan 25, 2019 10:04:00 AM

Almost $6.5 Billion – that’s the loss faced by the multi-billion dollar digital advertising industry as per the report by ANA (Association of National Advertisers) last year.


Mobile ad fraud happens when advertisers pay for clicks from non-existent users. Fraudsters do this by falsely triggering ad impressions or clicks on mobile websites and apps with the help of bots and special codes which mimic the real user behavior.

In-app advertising fraud continues to be the fastest growing ad fraud rising at 800% according to data by DoubleVerify’s Fraud Lab. That’s because ads in mobile apps are rarely blocked by ad-blocking software. This provides an environment which is friendly not only to advertisers, but also to the fraudsters– a Catch 22 situation. In terms of OS, Android is generally considered more vulnerable to attacks compared to iOS due to its open-ended architecture.

Detecting the signs of a fraudster attack is tricky. While there are multitude types of ad fraud, few companies specialize in blocking and detecting fraudulent activities. Plus, no matter how smart we are, fraudsters are becoming more sophisticated, inventing new ways to exploit the system.

With the continuous growth of digital ad spend, ad fraud will keep haunting us for years to come. But worry not, we have fortified the fight against the ad fraud to protect our customers by creating a wall with the help of Integral Ad Science (IAS), one of the best solutions in the market.

Pocketmath has integrated with IAS to detect and block fraudulent activities before bidding. Using IAS as a pre-bid solution, we can avoid fraud altogether at the inception, instead of reacting and filtering it out after you have bought the impressions.

On average, around 31% of the traffic we are receiving from exchanges are tagged as invalid traffic and rejected immediately with the help of IAS.

Here are some ad fraud types which we frequently see:

Display Impression Fraud

Impressions are generated from a device or the same browser at a statistically significant inflated rate. 

High Risk App

Impression is from an app which has been flagged for high risk of invalid traffic. 

Masked IP

User IP does not match the IP and the associated ISP reported in the advertising transaction. 

High Risk IP

Impression is from an app which has been flagged for high risk of invalid traffic. 

Device ID Stuffing

Activity from a device which has connected to the internet via a statistically significant inflated number of different IP Addresses. 

Publisher Fraud

Publishers operating domains or apps which violate standard ad serving practices including, for example, stacked ads, high ad density and inflated impression counts. 














Mobile ad fraud is always a complicated issue and your most clicks or installs are likely fake. If you are not clear about these complexities, the best way to go is work with a trusted partner like Pocketmath.

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Shahanas Babu

Written by Shahanas Babu