学术活动

“一个烂苹果如何败坏整桶”：基于动态商业网络的企业欺诈检测

2025年7月22日（周二）

10:30-12:00

杜玮

中国人民大学

Corporate fraud detection is attracting renewed research interest in the era of Internet connectivity due to its increasing complexity, concealment, and long-term duration. Previous fraud detection methods have heavily relied on financial statements and demonstrated limited detection power. While network analysis has emerged as a promising technique, its full potential in corporate fraud detection remains largely untapped, thus missing out on the potential improvement of fraud detection power. Recognizing this significant research gap, we devise a novel framework named as NetDetect to jointly learn structural information and temporal changes in dynamic heterogeneous networks for effective and interpretable corporate fraud detection. NetDetect consists of two new modules—meta-path-based static network feature extraction (SNFE) and temporal network feature extraction (TemFE). We rigorously evaluate each module and the entire framework against state-of-the-art baselines using a unique dataset of Chinese listed companies with a 561K node network. Experiment results and a case study demonstrate that our framework can detect corporate fraud more accurately compared to baselines and offer good early-warning capability as well as results interpretability. Our research results have important implications for various stakeholders (e.g., auditors, investors, and regulators) to understand and contain corporate fraud risk. We also discuss contributions to the IS knowledge base with three design principles to guide the development of similar IT artifacts.

杜玮，中国人民大学信息学院经济信息管理系副教授，硕士生导师，担任经济信息管理系副系主任。入选北京市科协青年人才托举工程。主要研究领域为推荐系统、金融科技、知识图谱、电商平台数据分析等数据智能和信息系统应用，利用前沿的人工智能和大数据技术解决管理决策中的复杂问题，在Decision Support Systems (DSS)、International Journal of Electronic Commerce (IJEC)、Scientometrics、Internet Research (IR)等国际期刊和ICIS、HICSS、PACIS等国际会议上发表研究论文多篇。任Informs JOC、IJEC、DSS、Scientometrics、IR、ECR等多个国际期刊和信息系统领域国际顶级会议同行评审员。申请专利十余项，多项授权，技术成果已应用于多个专利交易平台以促进科技成果转化。主持国家自然科学基金、教育部人文社科项目等科研项目多项。