BizBench: A Quantitative Reasoning Benchmark for Business and Finance
- URL: http://arxiv.org/abs/2311.06602v2
- Date: Tue, 12 Mar 2024 16:54:57 GMT
- Title: BizBench: A Quantitative Reasoning Benchmark for Business and Finance
- Authors: Rik Koncel-Kedziorski, Michael Krumdick, Viet Lai, Varshini Reddy,
Charles Lovering, Chris Tanner
- Abstract summary: BizBench is a benchmark for evaluating models' ability to reason about realistic financial problems.
We include three financially-themed code-generation tasks from newly collected and augmented QA data.
These tasks evaluate a model's financial background knowledge, ability to parse financial documents, and capacity to solve problems with code.
- Score: 7.4673182865000225
- License: http://creativecommons.org/licenses/by-nc-sa/4.0/
- Abstract: Answering questions within business and finance requires reasoning,
precision, and a wide-breadth of technical knowledge. Together, these
requirements make this domain difficult for large language models (LLMs). We
introduce BizBench, a benchmark for evaluating models' ability to reason about
realistic financial problems. BizBench comprises eight quantitative reasoning
tasks, focusing on question-answering (QA) over financial data via program
synthesis. We include three financially-themed code-generation tasks from newly
collected and augmented QA data. Additionally, we isolate the reasoning
capabilities required for financial QA: reading comprehension of financial text
and tables for extracting intermediate values, and understanding financial
concepts and formulas needed to calculate complex solutions. Collectively,
these tasks evaluate a model's financial background knowledge, ability to parse
financial documents, and capacity to solve problems with code. We conduct an
in-depth evaluation of open-source and commercial LLMs, comparing and
contrasting the behavior of code-focused and language-focused models. We
demonstrate that the current bottleneck in performance is due to LLMs' limited
business and financial understanding, highlighting the value of a challenging
benchmark for quantitative reasoning within this domain.
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