Scalarr continues the fight against mobile ad fraud, implementing machine learning for detection
The firm saved its customers over $22million in ad fraud refunds in 2019-2020
Customers include Joom, ZiMAD, Futureplay, Goodgame Studios, Huuuge Games, TextNow and Gamehive
Funding will be used to develop new products to target markets beyond mobile ad fraud and reach new geographies
Scalarr, the machine learning-based ad fraud prevention firm, announces a $7.5 million Series A round led by the European Bank of Reconstruction and Development (EBRD), with participation from TMT Investments, OTB Ventures, and Speedinvest. Speedinvest and TMT participated in the seed round too.
Co-founded in 2016 by Inna Ushakova (co-founder and CEO) and Yuriy Yashunin (co-founder and CPO), Scalarr is a premium machine learning based anti-fraud solution that analyses impressions, click, install, and post-install data to detect ad fraud and prevent marketing losses. Scalarr’s proven solutions to analyse massive amounts of data have made it possible to detect up to 60% more fraud than traditional anti-fraud solutions in the market. It helps mobile marketers and app developers detect and mitigate all types of fraud regardless of their level of complexity, and detect new fraud types based on exhaustive research.
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With this new funding, Scalarr plans to expand its presence and operations in Asia, along with targeting new, much bigger programmatic advertising markets. With the recent announcement of its DeepView anti-fraud product, Scalarr analyses billions of data points to help Ad Exchanges, demand-side platforms (DSPs) and supply-side platforms (SSPs,) detect even the slightest anomalies in connected TV (CTV)/ over the top (OTT), web, and mobile traffic. The latter being Scalarr’s strongest focus to date. With CTV’s current hype (300% growth in 2020 where 7 out of every 10 sold TVs are connected devices), Scalarr is a front-runner in the competition as many anti-fraud products are relatively new or still in beta versions.
Scalarr’s technology saved its customers over $22 million in direct ad fraud refunds in 2020 and over 50 million losses were prevented. Ad fraud is a growing global problem, with a recent global economic study revealing that losses from digital advertising fraud have risen to $35 billion. The rise in fraud follows the onset of COVID-19, with advertisers facing increases in malvertising attacks and click fraud on paid search and paid social campaigns.
Scalarr helps clients scale traffic channels and upkeep return on ad spend (ROAS), all while being protected against fraud. Scalarr acts as an advanced layer of protection and detects up to 40% more complex types of fraud than other solutions in the industry. By identifying and blocking fraudulent ad placements, advertisers can lower their effective cost per install level up to 25% and generate 20% more installs for a given ad budget.
This year, Scalarr introduced the Scalarr Prevention Layer, a pre-bid ad fraud service that enables clients to stop fraud before bidding on impressions can save up to 37.5% of the ad budget before traffic even gets to MMPs. Certainly, in the post-iOS 14 era, this is the most effective fraud prevention solution for the IDFA updates that will be implemented in early 2021. Scalarr’s Prevention Layer strengthens the Scalarr Protection Suite that also includes the Scalarr Detection Layer. This second layer includes an AI detection that can identify the most sophisticated fraud in already attributed installs.
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Inna Ushakova, CEO and co-founder of Scalarr comments, “We are wholeheartedly committed to saving our clients from all kinds of fraud and crippling losses that permeate an entire industry. We’ve seen an alarming increase in fraudster activity, and to make matters more complex, IDFA’s implementation will open up the door to unwanted attribution risks, prompting even more fraud attacks.”
“That’s why we are constantly digging as deep as possible using robust analytics and multiple data sources, all with the goal of strengthening our service offerings portfolio, feeding our powerful algorithms, and advancing our vision of a more transparent mobile ecosystem.”
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