There’s a gaping hole in the ad tech industry. The culprit? Ad fraud.
Anyone involved in the ad tech industry has known for years about the inefficiency in the supply chain that involves publishers, brands, consumers, and fraudsters.
We’re at a turning point in the industry — where publishers and industry leaders are once again focused on tackling the seemingly unstoppable threat that is ad fraud.
Why is this discussion coming back into the spotlight?
There’s been a recent finding that at least (most likely more) 15% of all ad spend is simply vanishing into nothingness…
But we know where it’s really going, and it’s slightly more complicated than nothingness.
The ad tech supply chain is still infested with an increasingly intelligent new wave of fraudsters as well as inefficient middlemen that the industry is finally realizing is no longer needed.
We’ll be discussing what’s really causing these huge revenue gaps, as well as what changes will need to be made to ensure a fair fight in the war that is ad fraud, and the steps some companies are taking to do so.
What’s Causing the Revenue Gaps
Last year alone it was estimated that ad fraud could account for losses between $6 and $19 billion.
A huge number and one that experts think is still conservative.
This problem is so severe, that an entire sub-industry of Ad Fraud Prevention developed to address it.
However, despite the numerous companies and software therein, Ad Fraud losses continue to rise.
Why is this?
In short, companies were simply taking the wrong approach, and the right technology had not yet been developed to truly detect and dismantle fraud in real time.
The industry had long taken a human driven approach to fraud prevention. Kubient’s VP of Product, Chris Francia, for their ad fraud prevention platform explains,
“When ad impression data is generated, these companies take that data and give it to a bunch of humans who analyze it and say if it is fraud or not fraud. Those results get put into a machine and the machine feeds that data to lists that are used to spot the fraud next time it appears. It is all reactive, and isn’t a new tactic — it’s the same type of ‘AI’ that was prevalent in the 80’s.”
Breaking down even further, machine learning also operates in one of two ways:
There are two kinds of Machine Learning: Supervised and Unsupervised. Supervised relies on a human telling the machine what something is, while unsupervised is telling the machine the concept of something and then it goes and decides what fits into that concept.
What has previously inhibited the ad fraud prevention industry’s ability to effectively combat fraud, has been its reliance on supervised machine learning, which is frankly not enough to combat the unforeseen fraud trends.
Where is all this invalid traffic coming from?
There are large networks of fraudsters across the world that run global schemes of fraudulent traffic and money laundering. And unfortunately, today’s economy is ripe for just that — Driven by the cheapness of false traffic, the accessibility of anonymity and easy exits through Bitcoin and other cryptocurrencies.
Another recent trend in the ad fraud space is the promotion and sale of “Click Injection” kits which can be widely found on the dark web and within the circles of fraudsters.
These kits spoof user activities to fake ad engagement and steal revenue from both publishers and advertisers.
This growing accessibility of ad fraud, combined with inefficient methods of combatting it, has resulted in the deep hole the Ad Tech industry currently finds itself in.
What Needs to Change
It’s clear that something needs to change.
While many experts believe that it is “impossible” to completely eradicate the ad fraud problem, that does not mean we need to sit idly and wait for even more collective revenue to be stolen.
First things first, the ad tech industry must solve it’s lack of transparency within it’s supply chain and introduce a more connected network.
Current leaders in the ad fraud prevention space, namely White Ops, Index Exchange and more are joining other big programmatic players in focusing on supply chain transparency.
To do so, may require the banding of these networks to tackle emerging fraud schemes and trends with data collected by these networks, instead of separately biting off small pieces of the problem after the fact.
Beyond transparency, innovation in the ways fraud is detected and actively fought against is crucial to gaining the upper-hand, which is what Kubient’s team has been hard at work actively building.
Introducing KAI
KAI, Kubient’s emerging Ad Fraud Prevention platform is a hybrid when it comes to machine learning and artificial intelligence — utilizing both the human element and the machine element in deciding what was fraud.
The unsupervised machine learning, which powers KAI, is what really separates the platform from its peers. The first real life example of this came in October of 2019, when KAI started flagging traffic as fraudulent that to the rest of the team, simply wasn’t…
“We found it really odd, because we looked at the data manually and it looked like clean traffic, so we thought it could be a false positive. But as we dug deeper, we discovered that it was actually a new kind of fraud, and the machine knew it before we did,” Chris Francia explains.
This new fraud was called synthetic traffic or SynthNet, which was a type of automated traffic that originates from a centrally controlled system instead of a network of bots.
It’s these types of networks that continue to cripple the ad tech industry, despite billions of dollars being poured into inefficient prevention tactics. And KAI’s team is confident that it will catch more and more emerging fraud schemes as they happen.
However, it’s important to note that KAI will not act as a gatekeeper for the ad fraud prevention space, in reality, they’re hoping for the exact opposite.
The more networks that can allow KAI’s system into their platforms, and the more that these ad prevention platforms become connected and transparent, the greater the industry as a whole benefits.
“It’s only going to get smarter — the more data it sees, the more patterns it analyzes, the more powerful and accurate it becomes.”
Conclusion
Ad Fraud is not going to be stopped overnight — it’s been a very long fight thus far, and it is only getting started.
That being said, the outlook for the future is positive. With the growing urgency of industry leaders to make serious changes to the ad tech supply chain, combined with daily innovations that emerging tech like KAI are making, the ad tech industry has a fighting chance in the war of Ad Fraud.
Interested in learning more about KAI? Check out the full story behind the platform and the team who built it.
