Paper Number

ECIS2026-1327

Paper Type

SP

Abstract

Generative AI (GenAI) has significantly boosted financial analysts’ efficiency by reducing search costs and automating repetitive tasks. For example, Bloomberg’s AI-powered Earnings Call Summaries, developed using FinLLM, allow analysts to quickly extract key insights from conference calls, streamlining report preparation. While previous research has shown that the individual adoption of GenAI can have both positive and negative effects depending on how reduced search costs are utilized, our study extends this analysis to the equity market. Our preliminary findings show that information asymmetry measures such as consensus error and forecast dispersion reveal a significant increment after the introduction of AI-Generated Earnings Call Summaries (AIGECS). Additionally, our results suggest that large-cap firms are more affected by AIGECS, further exacerbating information asymmetry. Overall, while GenAI improves individual efficiency, it does not necessarily reduce market-level information asymmetry.

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Jun 14th, 12:00 AM

Mitigate Information Asymmetry? The Impact Of AI-Generated Earnings Call Summaries

Generative AI (GenAI) has significantly boosted financial analysts’ efficiency by reducing search costs and automating repetitive tasks. For example, Bloomberg’s AI-powered Earnings Call Summaries, developed using FinLLM, allow analysts to quickly extract key insights from conference calls, streamlining report preparation. While previous research has shown that the individual adoption of GenAI can have both positive and negative effects depending on how reduced search costs are utilized, our study extends this analysis to the equity market. Our preliminary findings show that information asymmetry measures such as consensus error and forecast dispersion reveal a significant increment after the introduction of AI-Generated Earnings Call Summaries (AIGECS). Additionally, our results suggest that large-cap firms are more affected by AIGECS, further exacerbating information asymmetry. Overall, while GenAI improves individual efficiency, it does not necessarily reduce market-level information asymmetry.

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