Numbers Don’t Speak for Themselves: How LLMs Interpret the Soul of Financial Reports
In finance, the devil isn’t just in the details—it’s in the narrative. That’s what makes this new study by Md Talha Mohsin both timely and essential: it directly evaluates how five top-tier LLMs—GPT-4, Claude 4 Opus, Perplexity, Gemini, and DeepSeek—perform in interpreting the most linguistically dense and strategically revealing part of corporate disclosures: the Business section of 10-K filings from the “Magnificent Seven” tech giants. Rather than focusing on raw numbers or sentiment snippets, the study asks: can these LLMs extract strategic intent, infer risk, and assess future outlooks the way human analysts do? ...