All inventory across GumGum’s uniquely brand safe ad exchange will be shielded by MediaGuard, White Ops’ best-in-class pre-bid ad fraud protection.
SANTA MONICA, Calif. — GumGum, Inc., an artificial intelligence company specializing in solutions for advertising and sports, announced it has selected White Ops’ pre-bid prevention product, MediaGuard, to bring the world’s most robust anti-fraud protection to the GumGum programmatic advertising exchange. The exchange – which already includes integral patented brand safety and contextual targeting technologies – will now deploy White Ops’ MRC accredited fraud prevention across its entire inventory.
@GumGum partners with @WhiteOps, adding highest-level fraud protection to GumGum’s entire #computervision powered brand safe ad exchange inventory #brandsafety #programmatic #cybersecurity
“We’ve always had a safety first mentality, hence our investment in computer vision and NLP contextual analysis brand safety technology,” said GumGum VP of Programmatic Adam Schenkel. “But safety isn’t just about feeling secure about where ads are placed. It’s also about feeling secure that ad dollars are well spent – that, when ads are placed, they’re being seen by real live consumers. White Ops is the best in the business at identifying and blocking non-human traffic, so this partnership is helping realize our goal of delivering the absolute safest media buying solution possible.”
The announcement of the partnership comes at just the right time for an industry facing a growing range of threats. Brand safety and fraud are two of the biggest. A 2018 GumGum study found that 90 percent of marketers consider unsafe contexts for ad placements a serious problem in the industry. The 2019 Bot Baseline report, released by White Ops and the ANA (Association of National Advertisers), found that although projected losses to ad fraud is down 11 percent in two years, cybercriminals are now leveraging even more sophisticated ad fraud schemes such as tactics that mimic human behavior, fake premium publisher inventory and evade traditional detection techniques.
White Ops’ MediaGuard pre-bid prevention API is a machine-learning algorithm that learns and adapts in real-time from White Ops advanced bot detection techniques to accurately predict and block bot driven ad requests before a buyer has the opportunity to bid on them. This “upstream” elimination of fraudulent ad requests results in better performance for advertisers and yield for publishers.
“Cybercrime becomes more advanced and because of that, ad fraud persists in new, creative forms,” said Michael Tiffany, President and Co-Founder of White Ops. “Protecting against these tactics requires a comprehensive, dynamic and adaptive prevention solution. By implementing MediaGuard pre-bid fraud prevention, GumGum has reaffirmed its commitment to giving its advertisers and publishers real peace of mind when it comes to the validity of ad impressions.”
GumGum’s inventory – which was protected by White Ops’ post-bid product FraudSensor for the past three years – has been protected by MediaGuard since Q1 of this year. Buyers and sellers on GumGum’s exchange will see no change in inventory pricing.
About GumGum:
GumGum is an artificial intelligence company with a focus on computer vision and natural language processing. Our mission is to solve hard problems by teaching machines to understand the world. Since 2008, the company has applied its patented capabilities to serving media-related industries, including advertising and professional sports. For more information, please visit www.gumgum.com.
About White Ops:
White Ops is a cybersecurity company that protects the Internet from malicious bot activity. Globally, software-as-a-service from White Ops determines the validity of nearly 100 billion transactions per day on behalf of over 200 customers. Our proactive adaptation, Internet-scale, and multi-layered methodology have made us the platform of choice for some of the largest and most forward-thinking platforms and brands. For more information, visit www.whiteops.com.
