Innovative Research on Intelligent Financial Reporting Generation and Analysis Based on Generative AI

Purpose - In recent years, generative AI has shown great potential in the fields of natural language generation and data analysis. By automating the generation of high-quality financial reports, identifying data trends, and assessing risks, it has addressed the time-consuming, delayed, and subjective nature of traditional reporting. This article aims to explore the application value and challenges of generative AI in intelligent financial management and to provide practical guidance for the intelligent financial management of enterprises. Design/Methodology/Approach - This paper employs a literature review and case study analysis to systematically review the technological development and current application status of generative AI in the field of intelligent financial reporting. It verifies the practical effects through typical corporate cases. Combining the two methodologies, it delves into the advantages, challenges, and directions for improvement of generative AI, providing theoretical support and empirical evidence for its practical application in financial management. Findings - The study finds that generative AI has significant advantages in efficiency, accuracy, and data insight capabilities in the generation and analysis of intelligent financial reports. It also identifies key challenges in the application of generative AI. Through the rational application of generative AI, enterprises can greatly improve financial management efficiency and decision-making quality. However, to achieve large-scale application, continuous improvement in technology and policy support is needed in areas such as data privacy protection, model reliability, and regulatory compliance. Research Implications - The innovative application of generative AI in the field of financial reporting provides a new perspective for academic research, brings intelligent development tools for enterprises, and presents new challenges and opportunities for government and social management. Through the collaborative advancement of technology development, policy regulation, and public education, generative AI is expected to achieve efficient, safe, and sustainable development at multiple levels.