How does Quantcast describe its fraud capability?
At Quantcast, we rely on our live data set and machine learning capabilities to combat fraud and promote brand safety. In addition, we communicate directly with the ad exchange, which allows us to evaluate opportunities autonomously rather than relying on third parties to filter.
We have a three-pronged approach:
Proactive: Our systems carefully weigh opportunities against potential fraud and brand safety criteria before bidding--in fact, we filter out an average of 20-25% of requests pre-bid. 1) The team leverages our insight into live audience behavior across the internet to discern the differences between human and non-human traffic. We model fraud using these signals and use these models to detect and reject suspicious opportunities--including spoofed sites.
Reactive: Not all fraud and brand safety issues can be detected beforehand. We respond rapidly and thoroughly to correct issues when a customer or partner alerts us of a fraud or brand safety Issue. In cases of fraudulent placements or placements that violate brand safety specifications, we add them to block lists and thoroughly investigate them to avoid any repetition in the future.
Collaborative: We work with companies across the real-time bidding ecosystem, like SSPs/ Exchanges and trade bodies such as IAB’s Trustworthy Accountability Group (TAG), to identify and help create industry-wide blocks of inappropriate or miscategorized inventory. We also integrate with content verification vendors for additional control over both fraud and brand safety. This collaboration enables a tracking tag to be placed into creative, giving visibility into exactly where each ad is served and even allowing for the placement of blocking tags so ads are NOT served if environments do not stringently meet all brand safety and anti-fraud criteria.