Risk-Averse and Optimistic Advertiser Incentive Compatibility in Auto-bidding

The rise of auto-bidding in online advertising has created new challenges for ensuring advertiser incentive compatibility, particularly when advertisers delegate bidding to agents with high-level constraints. One challenge is the multiplicity of equilibria with reported constraints. Alimohammadi et al. (2023) proposed a notion of Auto-bidding Incentive Compatibility (AIC) which serves to highlight that standard auctions may not incentivize truthful reporting of these constraints. However, their definition of AIC is very stringent as it requires that the worst-case outcome of an advertiser's truthful report is at least as good as the best-case outcome of any of the advertiser's possible deviations. In this paper, we introduce two refined and relaxed concepts: Risk-Averse Auto-bidding Incentive Compatibility (RAIC) and Optimistic Auto-bidding Incentive Compatibility (OAIC). RAIC (OAIC) stipulates that truthful reporting is preferred if its least (most) favorable equilibrium outcome is no worse than the least (most) favorable equilibrium outcome from any misreport. We demonstrate that SPA satisfies both RAIC and OAIC. These findings clarify SPA's incentive properties under auto-bidding, specifically regarding advertiser perspectives on equilibrium selection.

In online advertising, advertisers often use automated bidding systems (auto-bidders) to buy ad space while sticking to constraints like a target cost-per-acquisition (tCPA). This paper explores whether standard ad auctions actually encourage advertisers to be truthful to their auto-bidders about these constraints. Previous research suggested that standard auctions might give advertisers a reason to lie about their targets. However, by looking at how advertisers evaluate multiple possible outcomes—either optimistically expecting the best or cautiously expecting the worst—we find a different result. We show that popular auction formats, specifically the Second-Price Auction, actually do a good job of encouraging truthful reporting under these realistic conditions. Ultimately, this means ad platforms may not need to completely overhaul their current auction systems to handle auto-bidders effectively.