Zujie Wen

Papers

Total Citations

H-Index

About

Dr. Zujie Wen is a leading researcher in artificial intelligence and financial security, with a focus on developing intelligent systems to combat payment fraud. Their most cited work, "IFDDS: An Anti-fraud Outbound Robot" (2021), introduces a novel framework that leverages conversational AI to reduce false positives in fraud detection. By deploying an outbound robot to verify suspicious transactions, Dr. Wen’s system minimizes unnecessary payment blocks while maintaining robust security—a critical balance in modern e-payment ecosystems. This contribution addresses a pressing challenge in internet finance, where over-cautious risk models often inconvenience legitimate users. With 2 citations, this paper has already influenced discussions on human-AI collaboration in fraud prevention. Dr. Wen’s research bridges natural language processing and risk management, offering scalable solutions for real-world financial platforms. Their work underscores a commitment to designing ethical, user-centric AI that enhances trust in digital transactions. As fraud tactics evolve, Dr. Wen continues to pioneer adaptive systems that protect consumers without compromising convenience, making them a notable voice in the intersection of AI and cybersecurity.