financial-fraud

FraudSociety 是首个联合建模信息与金融动态的 LLM 智能体仿真系统，用于模拟金融诈骗经济并评估反欺诈干预策略的有效性。

Discusses methods to protect AI agents from being used in financial fraud schemes.

This paper proposes a graph neural network framework for financial fraud detection that integrates transaction records and identity information into node attributes, employs a multi-layer message passing mechanism, and uses weighted supervision and structural consistency regularization to improve risk scoring and probability calibration. Experiments on a public dataset show the method outperforms existing approaches.