The Equation: How ChatGPT Revealed ‘Bloat’ in Corporate Disclosures

In a sample of US companies’ annual reports from recent years, the management discussion and analysis section contained almost 20,000 words on average. Not all investors have the time and expertise to make sense of so much text, which raises the question: Does the MD&A section need to be so long? Chicago Booth PhD student Alex G. Kim and Booth’s Maximilian Muhn and Valeri Nikolaev used ChatGPT to summarize MD&A disclosures, as well as transcripts of earnings conference calls, and their findings suggest that the answer is no. The researchers measured text “bloat” by calculating the difference in word count between the original document and what ChatGPT determined to be its optimal summary length—which trades off “signal” (relevant) and “noise” (redundant) words. The disclosures analyzed were bloated by about 70 percent, they find, indicating a high amount of relatively uninformative content. To learn more, read “ChatGPT Could Help Investors Make More Informed Decisions.”