| | --- |
| | license: cc-by-3.0 |
| | tags: |
| | - agent |
| | - workflow |
| | - multimodal |
| | - spreadsheet |
| | - pdf |
| | - image |
| | - code |
| | - finance |
| | - accouning |
| | modalities: |
| | - text |
| | - spreadsheet |
| | - pdf |
| | - image |
| | - code |
| |
|
| | configs: |
| | - config_name: Finch_Dataset_All |
| | data_files: |
| | - split: test |
| | path: |
| | - finch_workflows_test.jsonl |
| | --- |
| | |
| |  |
| |
|
| | # Finch: Benchmarking Finance & Accounting across Spreadsheet-Centric Enterprise Workflows |
| |
|
| | This repository contains the dataset for **Finch**, an enterprise-grade benchmark for evaluating an agent’s ability to work like a skilled finance & accounting expert (work IQ) on real-world professionel workflows. |
| |
|
| | * **Paper**: _to be added_ |
| | * **Project Page**: https://huggingface.co/datasets/FinWorkBench/Finch |
| | * **Code**: https://github.com/FinWorkBench |
| |
|
| | --- |
| |
|
| | ## Dataset Description |
| |
|
| | Finch focuses on **messy and long-horizon finance & accounting workflows** that span: |
| |
|
| | > data entry/import, structuring/formatting, web search, cross-sheet/file retrieval, calculation, financial modeling, validation, translation, visualization, and reporting. |
| |
|
| | The workflows are derived from **real-world enterprise workspaces** (primarily Enron, as well as corporations in the EUSES Corpus, investment and securities companies, World Bank, Canadian/British government agencies, and more), including: |
| |
|
| | - Enterprise **email threads** where collaborators naturally describe, discuss, and track workflows |
| | - Large and messy **spreadsheets** with multimodal artifacts including text, tables, formulas, charts, pivots, images, etc |
| | - Interlinked **PDFs and documents** that provide additional business context |
| |
|
| | We adopt a three-step workflow labeling process: |
| |
|
| | 1. **Inducing workflow types and instances** from real collaborative context in **enterprise email threads** (Enron Corpus: 500,000 emails from 150 executives and employees). |
| | 2. **Deriving concrete workflow instances** by analyzing changes across **spreadsheet versions** (15,000 versioned spreadsheets from Enron and EUSES) and designing workflows based on high-quality artifacts from investment and securities companies, World Bank, Canadian/British government agencies, WideSearch, Dabstep, and more. |
| | 3. **Conductin meticulous expert annotation** of task instructions, input files, and reference outputs, involving hundreds of hours of expert work. |
| |
|
| | This process yields **172 enterprise-grade workflows—primarily multi-task composite**, involving 1,710 spreadsheets and 27 million cells, capturing the intrinsic **compositional, messy, multimodal, and collaborative nature** of real-world finance & accounting work. In this release, we provide full annotations for the first 72 workflows, with the remaining 100 to be released in a subsequent update. |
| |
|
| | Experiment results show that even frontier agents (GPT 5.1 Pro and Claude Sonnet 4.5 Pro) solve fewer than 40% of the workflows, revealing a substantial performance gap for real-world enterprise scenarios. |
| |
|
| | --- |
| |
|
| | ## 📁 Dataset Structure |
| |
|
| | The instruction-tuning corpus is released in **JSONL** format. |
| | Each line corresponds to one **workflow-centric example**: |
| |
|
| | ```json |
| | { |
| | "id": "<workflow identifier>", |
| | "instruction_en": "<English task instruction for a finance & accounting workflow>", |
| | "source_files": ["<input file name>", "..."], |
| | "source_files_urls": ["<input file download URL>", "..."], |
| | "reference_outputs": { |
| | "files": ["<reference output file name>"], |
| | "text": "<textual reference output>" |
| | }, |
| | "reference_file_urls": ["<reference output file download URL>"], |
| | "task_type": "<task category (e.g., reporting, modeling)>", |
| | "business_type": "<business domain (e.g., budgeting, trading)>" |
| | } |
| | ``` |
| | --- |
| |
|
| | ## 📣 Feedback & Issues |
| |
|
| | If you find any issues with the dataset or have suggestions, please open a discussion in the **Community** tab — we value your feedback! |
| |
|
| | **📧 Contact:** finworkbench@gmail.com |
| |
|
