<p>The problem is really huge; it would cost $44B to marketers until the end of 2022 according to projections from Statista. Digital ads displayed on smart TVs are largely unmonitored at the moment due to the algorithmic complexity of fraud detection for such types of traffic. This is multiplied by the large number of weaknesses of SSAI technology which is broadly used for creating such ads. As a consequence, very often even primitive types of fraud like creating \’virtual TVs\’ using cheap laptops, as well as running ad views and clicks or bundle spoofing, remains unnoticed.</p> <p> </p> <p>This market is very young, it’s not well regulated and that is why fraud keeps growing here. With this in mind, marketers must keep a firm eye on the situation if they hope to plug what can be serious financial leaks. Building multi-layered ML platforms could definitely help to address this problem effectively, but this is only possible with a vast amount expertise and domain knowledge.</p>
<p>The problem is really huge; it would cost $44B to marketers until the end of 2022 according to projections from Statista. Digital ads displayed on smart TVs are largely unmonitored at the moment due to the algorithmic complexity of fraud detection for such types of traffic. This is multiplied by the large number of weaknesses of SSAI technology which is broadly used for creating such ads. As a consequence, very often even primitive types of fraud like creating \’virtual TVs\’ using cheap laptops, as well as running ad views and clicks or bundle spoofing, remains unnoticed.</p> <p> </p> <p>This market is very young, it’s not well regulated and that is why fraud keeps growing here. With this in mind, marketers must keep a firm eye on the situation if they hope to plug what can be serious financial leaks. Building multi-layered ML platforms could definitely help to address this problem effectively, but this is only possible with a vast amount expertise and domain knowledge.</p>