The Evolving Fraud Landscape
In 2015–2016, the fraud problem was already notable, but the industry was dealing with mostly primitive types of fraud, such as click-spamming and click-injections, according to Inna Ushakova, CEO & Co-founder of Scalarr. While Ushakova says these types of fraud are still common, “smart fraud” is the newest threat were smart bots or sophisticated bots can fully emulate user behavior and even make in-app payments. Ushakova also considers modified click-spamming as a form of smart fraud. “This year, we have seen significant growth in mixed traffic, which is one of the most insidious types of fraud these days,” she explains. “You might be facing click-spamming mixed together with bot traffic. From the developers’ point of view, it may look unsuspicious because of click-spamming, but in fact, this is a prime example of disguised fraud.” Ultimately, the biggest problem with fraud these days is that there’s so much money in fraud that perpetrators are incentivized to find new ways to fraud game developers as old mechanisms stop working.
With the evolving threat of new fraud types, Goodgame Studios’ scripts and anti-fraud tools were only catching primitive types of fraud. The developer then decided to survey the market for more advanced tools and came across anti-fraud solutions based on machine learning algorithms, leading their discovery of Scalarr.
Scalarr uses machine learning and big data algorithms to fight app install ad fraud primarily because of their ability to analyze a huge number of metrics and interrelations between them. This allows Scalarr to make more efficient analysis than manual human or rule-based techniques, which are still an integral part of most solutions. The end result? By reducing the number of false-negatives and false-positives, Scalarr’s accuracy is currently up to 97%, according to Ushakova.