A popular academic paper from The University of Chicago Booth School of Business on the use of LLM’s in analysis of Financial Statements (May 2024). 

Abstract: “We investigate whether an LLM can successfully perform financial statement analysis in a way similar to a professional human analyst. 

We provide standardized and anonymous financial statements to GPT4 and instruct the model to analyze them to determine the direction of future earnings. 

Even without any narrative or industry- specific information, the LLM outperforms financial analysts in its ability to predict earnings changes. The LLM exhibits a relative advantage over human analysts in situations when the analysts tend to struggle. 

Furthermore, we find that the prediction accuracy of the LLM is on par with the performance of a narrowly trained state-of- the-art ML model. LLM prediction does not stem from its training memory. Instead, we find that the LLM generates useful narrative insights about a company’s future performance.