A University of Chicago study reveals that generative AI surpasses financial analysts in predicting earnings by 8%, relying only on balance sheets and income statements. While AI is increasingly used in finance, combining AI’s efficiency with human expertise is suggested for more precise forecasts.
AI Outperforms Financial Analysts in Earnings Predictions
A study conducted by Alex Kim, Maximilian Muhn, and Valeri Nikolaev at the University of Chicago found that generative AI outperformed financial analysts in predicting earnings by an 8% margin. The AI model achieved this without using contextual data like sectoral issues or changes in personnel, relying solely on anonymized balance sheets and income statements.
Banks, hedge funds, and wealth managers are increasingly relying on AI, primarily for routine tasks such as transcribing earnings calls, summarizing data, and analyzing text. These tools are helping to eliminate human error and save time.
Although the model’s success highlights its potential, it’s suggested that a hybrid approach, combining strengths of both AI and human analysts, provides the most accurate forecasts. This indicates that there’s still room for human expertise alongside AI in financial sectors.
