From Transcripts to Insights: Uncovering Corporate Risks Using
  Generative AI
Alex Kim Maximilian Muhn Valeri Nikolaev
We explore the value of generative AI tools, such as ChatGPT, in helping
investors uncover dimensions of corporate risk. We develop and validate
firm-level measures of risk exposure to political, climate, and AI-related
risks. Using the GPT 3.5 model to generate risk summaries and assessments from
the context provided by earnings call transcripts, we show that GPT-based
measures possess significant information content and outperform the existing
risk measures in predicting (abnormal) firm-level volatility and firms' choices
such as investment and innovation. Importantly, information in risk assessments
dominates that in risk summaries, establishing the value of general AI
knowledge. We also find that generative AI is effective at detecting emerging
risks, such as AI risk, which has soared in recent quarters. Our measures
perform well both within and outside the GPT's training window and are priced
in equity markets. Taken together, an AI-based approach to risk measurement
provides useful insights to users of corporate disclosures at a low cost.