Datasets:

cofacto
/

IndFin-Bench

---
license: cc-by-nc-4.0
task_categories:
  - question-answering
language:
  - en
tags:
  - finance
  - indian-finance
  - benchmark
  - financial-qa
  - llm-evaluation
pretty_name: IndFin-Bench
size_categories:
  - n<1K
---
# IndFin-Bench: A Benchmark Grounded in Indian Financial Filings
  Published by [Cofacto](https://cofacto.ai) (formerly CompoundingAI), an AI research platform for Indian equities.
**IndFin-Bench** is a benchmark of 100 hand-curated questions sourced from the corporate filings of Indian listed companies. It is designed to evaluate how accurately LLMs can retrieve and reason over India-specific financial data.

Existing financial benchmarks like [FinBen](https://github.com/The-FinAI/FinBen) and [FinQA](https://github.com/czyssrs/FinQA) are built on US market data — SEC filings, 10-K reports, and earnings calls from American corporations. **IndFin-Bench fills this gap for the Indian market**, covering the Ind AS accounting landscape, SEBI disclosure formats, and cross-company reasoning over BSE/NSE-listed equities.

---
## Dataset Summary

| | |
|---|---|
| **Questions** | 100 |
| **Companies** | 100+ Indian listed firms |
| **Coverage** | FY23 - FY26 |
| **Source** | Annual reports, quarterly filings, investor presentations, BSE/NSE disclosures |
| **License** | CC-BY-NC 4.0 (with additional restrictions; see below) |

---
## Schema

| Field | Description |
|---|---|
| `Question_Num` | Unique identifier for the question |
| `Question` | Natural-language financial query grounded in official filings |
| `Complexity_Category` | 4-tier taxonomy from single-company single-fact to multi-company multi-fact |
| `Atomic_Fact` | Verified ground truth answer, sourced directly from official filings |

---
## Complexity Levels

| Category | Questions | What it tests |
|---|---|---|
| Single-Company, Single Fact | 38 | Retrieve one specific figure from one company's filing |
| Single-Company, Multiple Facts | 33 | Retrieve and synthesise multiple data points from a single company |
| Multi-Company, Multiple Facts | 20 | Compare or derive metrics across multiple companies |
| Multi-Company, Single Fact | 9 | Retrieve comparable figures across companies and perform comparison |

---
## Usage

```python
from datasets import load_dataset
ds = load_dataset("Cofacto/IndFin-Bench")
```
---
## Ground Truth

Each question has a corresponding **Atomic Fact** — a precise, minimal statement of the correct answer derived directly from official company filings. Every atomic fact has been manually verified against primary filings.

---
## Intended Use & Restrictions

This dataset is released under the **Creative Commons Attribution-NonCommercial 4.0 (CC BY-NC 4.0)** license.

**IndFin-Bench is strictly intended for evaluation and benchmarking of language models on Indian financial data.**

Typical allowed use cases include:
- Evaluating LLM performance on financial question answering
- Benchmarking retrieval-augmented generation (RAG) systems
- Comparing model accuracy across different complexity tiers

**Use of this dataset implies agreement with the following restrictions:**

- The dataset **must not be used for training, fine-tuning, or improving** any machine learning or AI models.
- This includes (but is not limited to):
  - Supervised training  
  - Fine-tuning or instruction tuning  
  - Reinforcement learning (RL / RLHF)  
  - Retrieval-augmented training pipelines  
  - Synthetic data generation derived from this dataset  

- The dataset must be used **only for evaluation purposes and not as a training corpus**.

---
## Citation

If you use IndFin-Bench in your work, please cite:

```
@dataset{cofacto2026indfinbench,
  title={IndFin-Bench: A Pioneering Benchmark Grounded in Indian Financial Filings},
  author={Cofacto},
  year={2026},
  url={https://huggingface.co/datasets/Cofacto/IndFin-Bench},
  license={CC-BY-NC-4.0}
}
```

## Links

- [Blog Post](https://cofacto.ai/benchmark)
- [Cofacto](https://cofacto.ai)

	---
	license: cc-by-nc-4.0
	task_categories:
	- question-answering
	language:
	- en
	tags:
	- finance
	- indian-finance
	- benchmark
	- financial-qa
	- llm-evaluation
	pretty_name: IndFin-Bench
	size_categories:
	- n<1K
	---
	# IndFin-Bench: A Benchmark Grounded in Indian Financial Filings
	Published by [Cofacto](https://cofacto.ai) (formerly CompoundingAI), an AI research platform for Indian equities.
	IndFin-Bench is a benchmark of 100 hand-curated questions sourced from the corporate filings of Indian listed companies. It is designed to evaluate how accurately LLMs can retrieve and reason over India-specific financial data.

	Existing financial benchmarks like [FinBen](https://github.com/The-FinAI/FinBen) and [FinQA](https://github.com/czyssrs/FinQA) are built on US market data — SEC filings, 10-K reports, and earnings calls from American corporations. IndFin-Bench fills this gap for the Indian market, covering the Ind AS accounting landscape, SEBI disclosure formats, and cross-company reasoning over BSE/NSE-listed equities.

	---
	## Dataset Summary

	\| \| \|
	\|---\|---\|
	\| Questions \| 100 \|
	\| Companies \| 100+ Indian listed firms \|
	\| Coverage \| FY23 - FY26 \|
	\| Source \| Annual reports, quarterly filings, investor presentations, BSE/NSE disclosures \|
	\| License \| CC-BY-NC 4.0 (with additional restrictions; see below) \|

	---
	## Schema

	\| Field \| Description \|
	\|---\|---\|
	\| `Question_Num` \| Unique identifier for the question \|
	\| `Question` \| Natural-language financial query grounded in official filings \|
	\| `Complexity_Category` \| 4-tier taxonomy from single-company single-fact to multi-company multi-fact \|
	\| `Atomic_Fact` \| Verified ground truth answer, sourced directly from official filings \|

	---
	## Complexity Levels

	\| Category \| Questions \| What it tests \|
	\|---\|---\|---\|
	\| Single-Company, Single Fact \| 38 \| Retrieve one specific figure from one company's filing \|
	\| Single-Company, Multiple Facts \| 33 \| Retrieve and synthesise multiple data points from a single company \|
	\| Multi-Company, Multiple Facts \| 20 \| Compare or derive metrics across multiple companies \|
	\| Multi-Company, Single Fact \| 9 \| Retrieve comparable figures across companies and perform comparison \|

	---
	## Usage

	```python
	from datasets import load_dataset

	ds = load_dataset("Cofacto/IndFin-Bench")
	```
	---
	## Ground Truth

	Each question has a corresponding Atomic Fact — a precise, minimal statement of the correct answer derived directly from official company filings. Every atomic fact has been manually verified against primary filings.

	---
	## Intended Use & Restrictions

	This dataset is released under the Creative Commons Attribution-NonCommercial 4.0 (CC BY-NC 4.0) license.

	IndFin-Bench is strictly intended for evaluation and benchmarking of language models on Indian financial data.

	Typical allowed use cases include:
	- Evaluating LLM performance on financial question answering
	- Benchmarking retrieval-augmented generation (RAG) systems
	- Comparing model accuracy across different complexity tiers

	Use of this dataset implies agreement with the following restrictions:

	- The dataset must not be used for training, fine-tuning, or improving any machine learning or AI models.
	- This includes (but is not limited to):
	- Supervised training
	- Fine-tuning or instruction tuning
	- Reinforcement learning (RL / RLHF)
	- Retrieval-augmented training pipelines
	- Synthetic data generation derived from this dataset

	- The dataset must be used only for evaluation purposes and not as a training corpus.

	---
	## Citation

	If you use IndFin-Bench in your work, please cite:

	```
	@dataset{cofacto2026indfinbench,
	title={IndFin-Bench: A Pioneering Benchmark Grounded in Indian Financial Filings},
	author={Cofacto},
	year={2026},
	url={https://huggingface.co/datasets/Cofacto/IndFin-Bench},
	license={CC-BY-NC-4.0}
	}
	```

	## Links

	- [Blog Post](https://cofacto.ai/benchmark)
	- [Cofacto](https://cofacto.ai)