Google Ads fraud and artificial intelligence

Digital advertising fraud has become a major threat to the advertising industry. According to the National Advertisers Association (ANA) in the US, advertising fraud will cost companies an estimated USD $ 6.5 billion in 2017. A recent report by Juniper Research presents an even bleaker picture, estimating that advertisers will lose USD $ 19,000 million in fraudulent activities next year. This figure, which also includes advertising on mobile devices, will continue to increase, reaching USD $ 44,000 million by 2022.

The industry in the United States recently began looking for effective ways to mitigate the effects of advertising fraud. Unfortunately, the problem can only be mitigated because the bad guys are always one step ahead.

Most anti-fraud measures have focused on rules-based methods and these are effective ways to combat simple advertising fraud activities. However, advertising fraud is increasingly sophisticated and traditional measures to stop it are often inadequate today.

An approach based on artificial intelligence

As attempts at advertising fraud become more sophisticated and difficult to detect, our defense and fraud detection mechanisms must also evolve, and the correct way to deal with it is with algorithms constantly optimized with artificial intelligence.

An advertising fraud detection system based on artificial intelligence really begins with a rules-based approach as a basis, but through self-learning, it builds layers of defense that learn with every suspicious activity it detects. A model based on artificial intelligence also has the advantage of being able to see patterns in many more dimensions than a traditional system.

Traditional rule-based models generally analyze activity in one to three dimensions. A model based on artificial intelligence can analyze more than 80 dimensions at a time, which allows it to detect extremely sophisticated patterns of advertising fraud. With self-learning, models based on artificial intelligence can evolve as patterns of advertising fraud evolve than try to evade traditional systems.

In Nei Analytics we constantly work on new algorithms to detect new types of fraud or misuse of advertising, in order to help our customers with advertising fraud.

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