In the era of the digital economy, data has evolved into a new type of production factor. Agent technology acts as a critical variable that unlocks the potential of data factors and propels economic cycles toward a silicon-based model. Nevertheless, the trust deficit restricting agent deployment constrains data supply, blocking the pathway of leveraging agents to boost financial development and materialize the value of data factors.Against this backdrop,Research on High-Quality Datasets and Evaluation Benchmarks for Financial Industry Intelligent Agentsauthored by Assistant Professor Zonghan Wu from SAIFS has been selected for the Arts and Sciences Interdisciplinary Training Program of East China Normal University. Centered on dataset construction, this project establishes a full-chain framework covering demand cataloging, dataset development, evaluation benchmark formulation, and industrial verification. It accelerates the creation of high-quality datasets tailored to financial agents, thereby maximizing the multiplier effect of data factors in advancing high-quality financial growth.
Source：SAIFS,ECNU
