Financial Question Answering Dataset

8.3K financial reasoning questions over real S&P 500 earnings reports.

Unique: This dataset uniquely combines structured tables and unstructured text from SEC filings, requiring multi-step mathematical operations for accurate financial analysis.

vs others: Unlike other financial datasets, FinQA specifically tests both financial domain understanding and quantitative reasoning in a structured manner.

via “financial question answering and information retrieval”

* ⭐ 04/2023: [Instruction Tuning with GPT-4](https://arxiv.org/abs/2304.03277)

Unique: Combines financial domain understanding with question-answering capability, enabling interpretation of complex financial questions (e.g., 'What are the key risks to Apple's iPhone revenue?') and synthesis of answers from financial documents. Domain-specific training enables understanding of financial metrics, relationships, and implications that general QA models miss.

vs others: Achieves higher accuracy on financial QA tasks than general-purpose models because it understands financial terminology, metrics, and domain context, whereas general models require extensive prompt engineering and struggle with financial-specific reasoning.

via “financial-question-answering”