If we take a look at the ads money flow — we’ll see that all the stages of it are prone to fraud. So basically everyone starting from advertisers, agencies, networks to associates and publishers are at risk of losing their money to fraudsters. Advertisers are likely to lose budgets by buying fraudulent site visitors. Affiliates and networks are losing money by getting rejects, losing contracts and advertisers.
When a network gets a bad acceptance or an affiliate has a few assets that are suspicious — next time an advertiser would think twice to invest in such traffic and doubtless would choose another network. We use Unsupervised ML to detect new anomalies and suspicious patterns that may point out that fraudsters have come up with anything new. When something is detected — our data scientists begin to drill down the info to be mindful the character of every specific anomaly, to learn more about the source, and to find the pattern. If we see that it’s really a new sample or scheme — we develop new algorithms and strategies that shall instantly detect this new type of fraud. When the development is finished — we improve the platform.
It’s a relentless process that requires a lot of time and abilities, but we have the coolest data technological know-how team and our technologies are known for instant tracking new ad fraud patterns.