Fraud prevention

Minimize non-human spend

The prevalence of fraudulent players in today‘s ad environment is an unfortunate reality. Even trusted ad networks and premium publishers have significant amounts of their inventories delivered to fraudulent automated traffic and never actually seen by human consumers.

Admetrics Fraud Prevention can counter the problem by providing the necessary analytical insights to optimize display and video inventory towards non-fraudulent traffic.
Coverage

What types of fraud techniques does Admetrics Fraud Prevention address?

Bot traffic
Botnets (or other automated agents) posing as humans that view or click on display or video ads.
iFrame stuffing
Stuffing ads or content into a tiny pixel, so that they count as served, but never have a chance to be actually viewed by a human consumer.
Ad farming
Also called ghost sites or pseudo sites, Ad Farms are fraudulent web properties that only exist to host a massive amount of ads without providing content targeted to a human audience.
Ad injection
An in-browser attack in which ads are forced onto a website, displacing the initial web page content or overlaying on top of existing content or ads.
Ad stacking
Multiple ads are placed on top of each other, with only the top ad actually in view.
How it works

Algorithmic fraud risk assessment

Using a wide range of probabilistic and deterministic signals, Admetrics Fraud Prevention employs a multi-layered detection approach to calculate a risk score for every impression. We call this the ARPA score.

ARPA is algorithmic fraud risk assessment via machine learning based on a wide range of probabilistic and deterministic signals.

The ARPA metric can then be used to optimize spend, for example to limit the exposure of a campaign to placements with an assigned risk under, say 65%.
Referrer & domain tracking
Admetrics analyzes and qualifies referrer data of domains and iFrames to assign the fraud risk on domain level.
Hidden ad detection
Admetrics identifies fraudulent deliveries through techniques like ad stacking, iFrame stuffing, pixel stuffing and ad farming.
Viewability tracking
Admetrics leverages viewability tracking as an indicator for fraudulent traffic, for example identifying clicks from impressions that are not viewable or finding other common patterns of fraudulent impressions.
Reputation databases
Admetrics maintains its own blacklists of compromised IPs or devices. Additionally, we use industry standard, real-time databases of compromised clients, IPs and notorious proxies.
Classification of botnet traffic
Admetrics analyzes and qualifies incoming traffic for signals that indicate fraudulent intent, including spoofed user agents and browsers, abnormal behaviour or traffic patterns.
Classification of automated traffic
Admetrics differentiates between ad fraud botnets and benign automatic traffic (regular spiders and crawlers that are not employed to manipulate ad media).
Data Studio

Putting the data to use

If you‘re not exporting the data for use in other systems, you can use Admetrics Data Studio to directly access fraud metrics on domain level.

The basic set comprises ARPA metrics like share of fraudulent automated traffic, share of non-fraudulent automated traffic, share of high risk traffic and spend at risk.
Simple integration

Adding Fraud Prevention to your stack

Like all Admetrics solutions, Fraud Prevention works like a charm with other systems and vendors in proprietary technical ecosystems.

Possible applications are feed integrationsAPI integrations or real-time interfaces for use in the programmatic area, like pre-bid flagging towards non-fraudulent impressions.
Privacy

GDPR Compliance

Like all admetrics solutions, Fraud Prevention is built according to the privacy-by-design principle and conforms 100% to the strict requirements of the EU's new privacy regulation.

Fraud Prevention does not store or process PII data and does not rely on any other active tracking technology (Cookies, etc), so explicit user consent is not required.

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