The company said that it involves "a breakthrough in deep learning technology" that is capable of pinpointing potential fraud before the victim's money is …

There are many approaches to determining whether a particular transaction is fraudulent. From rule-based systems to machine learning models - each method tends to work best under certain conditions. Successful anti-fraud systems should reap the benefits of all the approaches and utilize them where they fit the problem best. The notion of networks and connection analysis in the world of anti-fraud systems is paramount since it helps uncover hidden characteristics of transactions that are not retrievable any other way. In this blog post, we will try to shed some light on the way networks are created and then used to detect fraudulent transactions.

"All of the large online travel companies spend a significant amount of resources fighting fraud," Shpilman explained. "Fraud has evolved over the years, and chargeback fraud, which used to be the primary type of fraud that people fought with, is just one of the many things we have to fight with [now]." Chargebacks and false positives can also take heavy tolls on online travel merchants' bottom lines. "Travel, in principle, is a fairly low-margin business [in which] the majority of the companies make anywhere between 2 [percent] and 15 [percent] -- maybe 20 percent -- of the turn- over [on] their net revenue," he said. Online travel platforms looking to stay competitive need to continually balance robust safety protections with seamless experiences for customers.

Machine learning is, as simple search for news can prove, a hot topic in the tech industry. Its varied applications make machine learning truly unique: from the existing ones, such as disease prediction or loan assessment, to future applications, like generating videos from photos or identifying pixelated faces, the list is virtually endless. Another important application of machine learning has to do with Internet security. More specifically, an issue that affects the mobile advertising industry: fraud. The rise in fraud is one of the greatest challenges currently that mobile video advertising has to face these days, as bots and other sources can have a negative impact on the advertisement's effectiveness.