AI RESEARCH
The Fundamental Limits of Fraud Detection in Card Payment Networks
arXiv CS.LG
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ArXi:2605.27557v1 Announce Type: new Card payment fraud detection is usually framed as a supervised classification problem. Although this approach has generated practical progress, improvement has remained incremental despite major advances in model architecture. We argue that this is not mainly a failure of function approximation or optimization, but a consequence of structural information impairments inherent to the payment ecosystem. We formalize card authorization as a sequential decision problem with delayed, censored, corrupted, and counterfactually missing feedback.