- Scalarr, a startup it uses machine learning to combat ad fraud.
- Scalarr raises $7.5 million in Series A funding.
- The company was founded by CEO Inna Ushakova and CPO Yuriy Yashunin.
- The startup’s products include AutoBlock, which to detect fraud before any advertiser bids on an ad.
Scalarr applies both unsupervised and semi-supervised machine learning algorithms to automatically detect and recognize fraud patterns from huge amounts of data. It analyzes hundreds of clicks, installs, and post-install event features and variables, thus effectively reducing the number of false-positive and false-negative errors. Overview, inspect, and prevent mobile app installation ad fraud with unsupervised machine learning capabilities before any damage is done.
Scalarr uncovers fraud attacks with 97% accuracy and completeness. It detects the acute correlations across multiple accounts together with a deep dive into individual campaign data. Thus, it differentiates and marks various types of fraud, including mixes and new fraud patterns.
Scalarr raises $7.5M for Mobile Ad Fraud.
Scalarr, a startup that says it uses machine learning to combat ad fraud, is announcing that it has raised $ 7.5 million in Series A funding. The company was founded by CEO Inna Ushakova and CPO Yuri Yashunin, who previously led mobile marketing agency Xena.
Ushkova told that while living in Xena, she felt that advertising fraud had increased to such an extent that it posed a real threat to her business. The team was not affected by any existing anti-fraud solutions, so it built its technology. Eventually, he completely shut down Xena and moved the entire team to Scalarr. While the big ad attributes the companies add anti-fraud products, they are not the center of attention. And historically, companies have tried to detect fraud through a ‘rules-based approach
Scalarr’s funding and its product
The European Bank of Reconstruction and Development led Scalarr’s Series A round. Also participation from TMT Investments, OTB Ventures, and SpeedbeforeAmong other things. The company will use the funds to expand its presence in Asia and continue to develop the product. The startup’s products include Autoblock, a fraud detection prior to an advertiser’s bids on an ad, and DeepView, which is used by EdTech platforms (including ad exchanges, demand-side platforms, and supply-side platforms) is.
Scalar says it can detect 60% more fraud than existing products on the market and it saved its customers $ 22 million in advertising fraud refunds in 2020. Ushkova largely attributed this to the startup’s widespread use of machine learning technology.
