An Economic Analysis of Online Ad Fraud Deterrence

Ad fraud is increasingly becoming a major concern in online advertising, with publishers being one of the key sources of fraudulent ad traffic. Although ad fraud deterrence is a critical problem from both technical and economic perspectives, past research has not considered their interplay. Our paper fills this critical gap by building a game-theoretic model wherein an ad network (an intermediary between publishers and advertisers) strategically leverages its technological tool (the configuration of a given fraud detection technology) and economic tool (the payment to publishers) to deter ad fraud and maximize profits effectively. Our analysis generates several interesting findings. For example, as the fraud detection technology and fraud generation techniques improve, we show that although the ad network needs to respond by making the technology configuration stricter to dampen fraud motives and admit less ad traffic, it may sometimes need to increase the payment. Furthermore, although many stakeholders advocate instituting strict legislation and policies to reduce malicious publishers, we show that this may sometimes fail to reduce fraud traffic and even hurt an ad network’s profit. In addition, our results provide other useful implications that present a new theoretical perspective on the incentive problems in ad fraud generation and detection. Our study also draws valuable insights for ad networks into implementing effective ad fraud deterrence policies and for advertisers to audit and monitor their ad campaign performance. This paper was accepted by Hemant Bhargava, information systems. Funding: S. Kumar thanks the Temple Center for International Business Education and Research for partially supporting this research. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2022.02201 .