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Technological advancements and the dynamics of the platform economy make rooting out fraud more complicated than it may seem.

With print media circulation and broadcast television viewership in free fall, a lot is riding on the online advertising space being able to take up the slack. The good news is, digital ad spend is booming: The global total for 2025 is expected to surpass $678 billion, at an annual growth rate of nearly eight percent.

The bad news? A good chunk of that money is chasing a mirage.

Online ad fraud—where ad publishers falsely inflate engagement metrics (impressions, clicks, etc.) to boost revenues—is a growing problem that . 

and , both professors in the information systems and operations management area at at �鶹��Ƶ, are researching how online ad networks, such as Google Ads, can improve upon existing anti-fraud methods. Their recently published paper in  explores deep-rooted dynamics of the online ad ecosystem that make eliminating fraud even more complicated than it may seem at first glance. The paper was co-authored by Subodha Kumar of Temple University.

The researchers used a game-theoretic model to replicate the interconnected decision-making of the three players involved: advertisers, publishers, and the networks that serve as go-between.

“The way the ecosystem works is that the platforms in the middle, the ad networks, shares the benefit from the transaction,” Chen explains. “People have been arguing whether the network is incentivized to put their best efforts behind deterring fraud, since the fraudulent traffic benefits the networks too. So we tried to create a model to capture this.”

“If the advertisers rely solely on the reports from the ad networks, they may be at risk. They should use third-party tools to audit the performance better.”

—Min Chen, information systems and operations management professor at the Costello College of Business at �鶹��Ƶ

In addition, the model incorporates the two main fraud deterrents that networks routinely use. One is technological—platforms can adopt tougher standards for fraud detection, widening the scope of suspicious activity that gets flagged. The other is economic—lowering payments to all publishers so as to disincentivize large-scale fraud.

Surprisingly, the researchers find that the online ad economy works best when the two approaches seem to be working at cross-purposes. A tightening in fraud detection technology, paired with high payments for publishers, may sometimes produce the best outcomes for advertisers, publishers, and networks, as the market evolves.

The reason is rooted in the imperfect nature of fraud detection. To be sure, detection systems are improving all the time, especially with the advent of AI. But fraudsters do their best to blend in and adapt, using technological tools that often outpace those of their pursuers. “You cannot catch all the fraud, and if you try, you are going to mis-detect a lot of non-fraud,” Chen says.

Tougher fraud detection, then, will always mean more false positives, no matter how good the technology gets. To counter this inherent unfairness that penalizes good and bad actors alike, the ad network’s payment to publishers need to go up. Otherwise, publishers may take their business elsewhere—especially those most valuable to the system, i.e. those that are trustworthy— thereby decreasing the advertisers’ valuation on ad traffic.

“These ad networks are kind of a unique system where you can be monetarily rewarded for being honest, or punished for being dishonest,” Ray says. “What we discover for this system is there can be a way in which we can give carrots to people, not just sticks.”

On a similar note, the researchers find that an attempt to purge “bad apple” advertisers from the system can backfire due to false positives. In fact, fraud can sharply increase if networks, believing they have solved the problem, relax their fraud detection standards and raise incentives for the remaining advertisers. “Since the publishers who produce the fraudulent traffic are fewer now, the ad network may no longer need to maintain a strict detection policy. This can encourage the remaining ones to commit much more fraud,” Chen explains.

To Ray and Chen, online ad fraud is, in at least one sense, no different from older forms of malfeasance that are found in all free societies. “We need to have some kind of mechanism for managing the level of fraud, because the fraud detection method is never going to be perfect, whether it’s financial fraud, accounting fraud, etc.,” Chen says.

But as an example of the contemporary platform economy, the online advertising ecosystem is also distinctive, in that its de facto regulatory authority has skin in the game. The ad networks’ mixed incentives—as both beneficiaries and inhibitors of fraud—can undermine integrity and trust within an already-compromised system.

“If the advertisers rely solely on the reports from the ad networks, they may be at risk,” Chen says. “They should use third-party tools to audit the performance better.”