---
title: Q1 2019 Ad Fraud Report
description: Report on the percentage of digital ad fraud within the programmatic system during Q1 2019 with device, global region, browser, and operating system data.
image: https://blog.fraudlogix.com/hubfs/Data%20Reports/Graphs/AdFraudByDeviceQ12019_NoBackground.png
---

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# Articles and Research

# Q1 2019 Ad Fraud Report

Posted by [Fraudlogix](https://blog.fraudlogix.com/author/fraudlogix) on May 21, 2019 12:15:00 PM

![](https://blog.fraudlogix.com/hubfs/Fraudlogix_Favicon.png)

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In [September 2018 we began reporting ad fraud statistics](https://blog.fraudlogix.com/12-percent-of-global-ad-traffic-fraudulent) for the programmatic ad space based on monthly data we collected. We then published our first Quarterly Ad Fraud Report with data from [Q4, 2018](https://blog.fraudlogix.com/q4-2018-ad-fraud-report). We're continuing this coverage with our Q1 2019 Ad Fraud Report, which includes data on which devices, browsers and operating systems are being used most for fraud and what areas of the world fraudulent traffic is originating from.

---

#### **Download a copy of this report.**

A PDF of our Q1 2019 Programmatic Ad Fraud Report is provided in the link below. 

[![Q1 2019 Ad Fraud Report](https://no-cache.hubspot.com/cta/default/2077077/7e38f416-333a-448a-992e-2643833b42c1.png)](https://cta-redirect.hubspot.com/cta/redirect/2077077/7e38f416-333a-448a-992e-2643833b42c1)

---

Below are some of the highlights from Q1 2019. Fraudlogix’s pixel-based technology regularly monitors data from 640+ million unique users, 1.2 billion unique devices, and 300+ million URLs and apps monthly. We map the latest devices, locations, bots, behaviors and hacking tactics that are being used by digital fraudsters.

## **14.7% of all ad traffic was fraudulent.**

Looking at digital ad traffic globally (all locations and all device types), we found that 14.7 percent of it was fraudulent, an 11 percent increase from Q4, 2018. The biggest increase in fraud came from desktop display traffic, which was 18.1 percent fraudulent, a 13.6 percent increase from Q4 2018. 

![AdFraudByDeviceQ12019_NoBackground](https://blog.fraudlogix.com/hs-fs/hubfs/Data%20Reports/Graphs/AdFraudByDeviceQ12019_NoBackground.png?width=600&name=AdFraudByDeviceQ12019_NoBackground.png)

## **23% of LATAM ad traffic was fraudulent - the highest among four global regions.**

Looking at all data during Q1 2019, broken down into four major global business regions \[Asia–Pacific, including India (APAC); Europe, the Middle East and Africa, including Russia (EMEA); Latin America, including Mexico (LATAM); and North America (NA)\], we found that ad traffic coming from the LATAM region had the highest percentage of fraud at 23.0%, followed by the EMEA region with 12.8%, North America at 12.0% and the APAC region with 6.2%.

![AdFraudbyRegionQ12019](https://blog.fraudlogix.com/hs-fs/hubfs/Data%20Report%20Images/AdFraudbyRegionQ12019.png?width=600&name=AdFraudbyRegionQ12019.png)

## **A majority of ad traffic came from Chrome browsers and 16% of it was fraudulent.**

Like in Q4 2018, Google's Chrome browsers accounted for 68 percent of all ad traffic, however, the percentage of fraudulent traffic jumped from 14 percent to 16 percent.  Internet Explorer again had the highest percentage of fraudulent traffic at 29 percent.

![AdFraudbyBrowserQ12019](https://blog.fraudlogix.com/hs-fs/hubfs/Data%20Report%20Images/AdFraudbyBrowserQ12019.png?width=600&name=AdFraudbyBrowserQ12019.png)

## **Devices running versions of Android 8 dominated - 13.8 percent of that ad traffic was fraudulent.**

In Q1 the most common operating system among devices was the Android 8 (20 percent), followed by devices running Windows 10 (16.3 percent). Ad traffic coming from Android 8 operating systems was 13.8 percent fraudulent. Ad traffic coming from Windows 7 operating systems was the riskiest - 21.1 percent of it was fraudulent.

![AdFraudbyOSQ12019](https://blog.fraudlogix.com/hs-fs/hubfs/Data%20Report%20Images/AdFraudbyOSQ12019.png?width=600&name=AdFraudbyOSQ12019.png)

## **Quarter Over Quarter Change: Q1 2019 and Q4 2018**

As we continue to track trends and data over time, we'll update the following chart:

![Q4vsQ12019](https://blog.fraudlogix.com/hs-fs/hubfs/Data%20Report%20Images/Q4vsQ12019.png?width=600&name=Q4vsQ12019.png)

**Keep an eye out for further insights.**

Keeping the industry updated on the latest data and threats we see in the digital ad community is important, so we we'll be publishing regular updates on ad fraud percentages as well as which countries, devices, browsers and operating systems are being taken advantage the most for [ad fraud schemes](https://blog.fraudlogix.com/the-biggest-ad-fraud-schemes-and-ad-tech-stories-of-2018). Stay tuned. 

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 Topics: [Research](https://blog.fraudlogix.com/topic/research)

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```json
// <![CDATA[
{						
"@context":"http:\/\/schema.org",						
"@id":"ad-fraud",						
"@type":"Thing",						
"description":"Any time engagement with an online ad has been forged to generate revenue.",	
"mainEntityOfPage":"http://wiki.fraudlogix.com/glossary/ad-fraud/",											
"name":"ad fraud",						
"alternatename": ["ad fraud","invalid traffic"],						
"sameAs":"https://en.wikipedia.org/wiki/Ad_fraud"						
					
}
// ]]>
```

```json
// <![CDATA[
{						
"@context":"http:\/\/schema.org",						
"@id":"bot",						
"@type":"Thing",						
"description":"A bot is a software application that’s programmed to run automated tasks over the internet. In terms of ad fraud, bots are often malware programmed to visit websites to view and interact with ads, which generates forged (fake) impressions, views, and clicks.",						
"mainEntityOfPage":"http://wiki.fraudlogix.com/glossary/bot/",						
"name":"bot",						
"alternatename": ["internet bot","web robot","WWW robot"],						
"sameAs":"https://en.wikipedia.org/wiki/Internet_bot"						
					
}
// ]]>
```

```json
// <![CDATA[
{						
"@context":"http:\/\/schema.org",						
"@id":"RTB",						
"@type":"Thing",						
"description":"In the online advertising space, RTB is the way programmatic ads are bought and sold on a per-impression basis – it’s the instantaneous auction of ad space that happens every time a user views a webpage that monetizes programmatically. Very basically, a user visits a website, which generates a bid request for the ad space on that page. The bid request contains information on that user (e.g., IP address, user agent, location, cookie information, etc.). Advertisers bid on the impression based on the information from the bid request and the winner of the auction gets their ad served to that user. This all happens in a fraction of a second. ",						
"mainEntityOfPage":"http://wiki.fraudlogix.com/glossary/rtb/",						
"name":"RTB",
"alternatename": ["real time bidding"],						
"sameAs":"https://en.wikipedia.org/wiki/Real-time_bidding"						
					
}
// ]]>
```

```json
// <![CDATA[
{						
"@context":"http:\/\/schema.org",						
"@id":"fraudulent-traffic",						
"@type":"Thing",						
"description":"Ad traffic that’s been generated by bots, malware, compromised devices, or other fraudulent means and is falsely masquerading as human traffic by visiting, viewing, and interacting with online ads.",						
"mainEntityOfPage":"http://wiki.fraudlogix.com/glossary/fraudulent-traffic/",						
"name":"fraudulent traffic",
"alternatename": ["fake traffic","invalid traffic","non-human traffic"]						

					
}
// ]]>
```

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			],
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			"@type":"Organization",
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	]
// ]]>
```

```json
// <![CDATA[
{
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  	"datePublished": "2018-10-09",
  	"description": "the percentage of fraudulent traffic from the ten countries (United Kingdom, United States, Spain, Brazil, Argentina, Mexico, France, Canada, Germany, Italy) with the highest volume of ad traffic observed.",
  	"name": "fraudulent traffic"
}
// ]]>
```

```json
// <![CDATA[
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  	"datePublished": "2018-10-09",
  	"description": "percentage of fraudulent traffic by device type (desktop device, mobile device, tablet device)",
  	"name": "digital ad traffic from fraudulent devices"
}
// ]]>
```