A Study of Intelligent Financial Report Generation Based on Deep Learning

School of Data Science, NingboTech University, Ningbo, China

surin@ldy.edu.rs

Abstract

In the contemporary era, with the astonishingly rapid development of artificial intelligence technology, the demand for intelligent financial report generation technology within the finance sector is burgeoning day by day. As technology advances, intelligent financial report generation demonstrates remarkable potential in multiple aspects. It can significantly boost efficiency, substantially cut down costs, and powerfully enhance decision support for financial operations. This study comprehensively reviews the value and significance of this field, taking into account a wide range of relevant papers. In line with previous research, it meticulously analyzes the mainstream methods, commonly utilized datasets, and evaluation criteria during the innovative process of financial report generation. Moreover, it thoroughly discusses the existing problems and potential solutions. The study reveals that even though deep learning has achieved substantial progress in this area, it still grapples with numerous challenges, such as issues related to data quality, model interpretability, and domain adaptability. For future research, it is crucial to concentrate on directions like multimodal data fusion, knowledge-enhanced modeling, and continuous learning. These efforts are expected to effectively promote the further development of intelligent financial report generation technology, enabling it to better serve the complex and dynamic financial industry.