发表机构
Business School, Central South University（中南大学商学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究提出双市场信号模型，揭示生成式AI降低伪造与验证成本时，信任因延迟验证吸引欺诈，形成自我限制的信任套利机制，并产生跨市场的暂时保护缺口。
AI 中文摘要
信任在延迟验证时可能吸引欺诈。我们开发了一个双市场信号模型，在该模型中，生成式人工智能降低了伪造、验证和定向成本。当伪造在验证之前变得有利可图时，声明可信度先下降后恢复。跨市场来看，更高的先验质量可能延迟验证，从而产生一个区间，在该区间内只有质量较低的市场进行验证。如果定向在此区间内变得有利可图，欺骗性卖家会进入质量较高但警惕性较低的市场，其进入最初可能逆转该市场的可靠性优势。流入也触发验证并阻止进一步进入。我们将这种自我限制机制称为信任套利。在生成式人工智能时代，信任因此可能产生一个内生但暂时的保护缺口，将欺骗行为跨市场转移。
英文摘要
Trust can attract fraud when it delays verification. We develop a two-market signaling model in which generative AI lowers fabrication, verification, and targeting costs. When fabrication becomes profitable before verification, claim credibility first falls and later recovers. Across markets, higher prior quality can delay verification, creating an interval in which only the lower-quality market checks. If targeting becomes profitable in this interval, deceptive sellers enter the higher-quality but less vigilant market, and their entry can initially reverse its reliability advantage. The inflow also triggers verification and deters further entry. We call this self-limiting mechanism trust arbitrage. In the age of generative AI, trust can thus create an endogenous but temporary protection gap that redirects deception across markets.
Comments11 pages, 1 figure. Author accepted manuscript. Published in Economics Letters
DOI：10.1016/j.econlet.2026.113234
