Is AI reasoning useful in finance?

Whether Large Language Models (LLMs) will result in a marginal productivity increase or a technological revolution largely depends on their ability to reason. LLMs with reasoning capabilities outperform vanilla ones on math and coding. However, it remains unclear whether such emergent abilities translate into improved economic insights. We evaluate state-of-the-art general-purpose reasoning-enhanced LLMs by OpenAI and DeepSeek on standard financial tasks: news sentiment and earnings direction prediction. Reasoning-enhanced models fail to demonstrate a significant advantage, while model size does. These findings indicate that improved reasoning does not necessarily translate into enhanced economic intuition, questioning their cost-effectiveness and practical utility in finance. Only finance-specific reasoning models yield a relatively modest increase in performance.