Study of Ethical Risks and Governance Framework of Generative AI in Financial Reporting Automation

Jing Wang

doi:10.54097/mb60fy75

Authors

Jing Wang

DOI:

https://doi.org/10.54097/mb60fy75

Keywords:

Generative AI, Financial Reporting, Ethical Risk, Governance Framework, Human-Machine Collaboration

Abstract

The rapid application of generative AI in financial reporting automation raises important ethical governance issues. This study reveals the three core risks of data security leakage, algorithmic bias amplification, and responsibility boundary blurring, and constructs a multi-level governance framework based on technical protection, compliance regulation, and process control. The study innovatively proposes a dynamic ethical assessment mechanism and emphasises the importance of collaborative human-machine supervision. Empirical analyses show that a sound governance system can effectively prevent ethical risks and provide practical guidelines for the healthy development of enterprise AI financial systems. The future research direction should focus on cross-border data governance and social responsibility balancing mechanism.

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