FinQA
A large-scale dataset for numerical reasoning over financial data with question-answering pairs written by financial experts, featuring complex numerical reasoning and understanding of heterogeneous representations with annotated gold reasoning programs for full explainability
Progress Over Time
Interactive timeline showing model performance evolution on FinQA
State-of-the-art frontier
Open
Proprietary
FinQA Leaderboard
3 models
| Context | Cost | License | ||||
|---|---|---|---|---|---|---|
| 1 |  Amazon | — | 300K | $0.80 / $3.20 | ||
| 2 | Amazon | — | 300K | $0.06 / $0.24 | ||
| 3 | Amazon | — | 128K | $0.03 / $0.14 |
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FAQ
Common questions about FinQA
A large-scale dataset for numerical reasoning over financial data with question-answering pairs written by financial experts, featuring complex numerical reasoning and understanding of heterogeneous representations with annotated gold reasoning programs for full explainability
The FinQA paper is available at https://arxiv.org/abs/2109.00122. This paper provides detailed information about the benchmark methodology, dataset creation, and evaluation criteria.
The FinQA leaderboard ranks 3 AI models based on their performance on this benchmark. Currently, Nova Pro by Amazon leads with a score of 0.772. The average score across all models is 0.720.
The highest FinQA score is 0.772, achieved by Nova Pro from Amazon.
3 models have been evaluated on the FinQA benchmark, with 0 verified results and 3 self-reported results.
FinQA is categorized under economics, finance, math, and reasoning. The benchmark evaluates text models.