FinCoT: Grounding Chain-of-Thought in Expert Financial Reasoning
Natapong Nitarach, Warit Sirichotedumrong, Panop Pitchayarthorn, Pittawat Taveekitworachai, Potsawee Manakul, Kunat Pipatanakul
2025-06-24
Summary
This paper talks about FinCoT, a special way to guide large language models in finance to think step-by-step like human experts when solving financial problems.
What's the problem?
The problem is that AI models often give shallow or incomplete answers in finance because they don't follow the detailed, expert reasoning processes that humans do.
What's the solution?
The researchers created structured prompts that include expert financial workflows and explicit steps, allowing the AI to break down problems and check its work along the way, making the AI's reasoning more accurate and aligned with financial experts.
Why it matters?
This matters because it makes AI better at understanding and solving complex financial problems, which helps improve decision-making, predictions, and explanations in the finance world.
Abstract
A structured chain-of-thought prompting method in financial natural language processing improves performance and reduces computational cost while enhancing interpretability.