Technology company AdTheorent has unveiled a new machine learning-driven infrastructure designed to eliminate ad fraud and deliver what it is calling the mobile ad industry's "first truly clean supply".
The solution uses a combination of data-driven algorithms and qualitative analysis to detect and remove fraudulent properties, tapping the firm's robust data-driven predictive modelling platform to help publishers avoid click fraud.
As well as using advanced machine learning capabilities to identify anomalies and aberrational behaviour that indicates fraud, the company conducts on-going qualitative reviews of mobile websites and apps within its network, focusing on identifying low value ad impressions that might slip through the web of statistical algorithms.
"Ad fraud undermines advertiser confidence in the efficacy of mobile advertising, this we have made a significant infrastructural investment to offer our advertisers supplemental protections that simply don't exist in the broader market," said James Lawson, managing partner and chief legal officer of AdTheorent.
"Fraud detection solutions are en vogue at the moment, but our strategy is not to re-skin existing third party verification offerings, which have limitations. Instead, AdTheorent data scientists and software developers continue to innovate towards both data-driven and qualitative solutions that will advance mobile advertising into its next phase."