Financial disclosure Synergy between generative AI and unstructured social data: a comparison between ChatGPT narrative synthesis and Facebook sentiment shocks.
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There is a gigantic change in the information presented under financial reporting where static and outdated paperwork is being replaced with more real-time and dynamic information. This paper examines how Generative AI (ChatGPT) and social media data that is not structured (such as Facebook) can be more transparent and predictive of corporate disclosures. Conventional reporting is all about retrospection of the audited statements that may be falling behind the reality on the ground and may be lacking the real-time market sentiments. In this work, I applied a comparative approach to research and triangulation of data to observe the way these techs can cooperate. By using ChatGPT, I discovered that it is an Internal Architect that reduces the time off reporting by approximately 40 percent and keeps documents structurally sound, IFRS compliant, as well as taking on anomalies. Facebook, in its turn, would be the External Sentinel, its sentiment peaks can be used as early warning signals of financial risk, and it regularly raises concerns regarding the troubles approximately 5.2 days before official impairment reports, or stock price changes. The lesson of the big picture is that hybridity between the AI-based story generation and the social media sentiment analysis is the key to the True and Fair View in the environment where information circulates rapidly. I would advise that the companies release data on social media risks, as well as implement AI-enhanced audits, to bridge the transparency gap
Keywords
ChatGPT, Generative Artificial Intelligence, Real-time Intelligence, Sentiment on Social Media, The Quality of Financial Reporting