BFSI-Bench

BFSI-Bench is a ground-truth benchmark for testing how well language models answer questions about India’s banking, financial services, and insurance (BFSI) rules.

In this domain, the correct answer often depends on circulars and regulations that change frequently, and the official sources (sites like RBI, SEBI, and IRDAI) can be hard to find, parse, and keep current. BFSI-Bench measures four capability areas:

• Jurisdiction-Aware Compliance: Disambiguate to the Indian context, or ask a clarifying question, instead of defaulting to U.S. or EU rules.
• Numerical Reasoning: Get finance math right, including EMI, interest, and TDS.
• Temporal Logic: Prefer currently applicable circulars and limits when the prompt does not specify a year.
• Red-Team Evasion: Refuse illegal financial workarounds and point users to legitimate channels.

Questions and gold answers are expert-written and checked against official Indian sources.

Name	ground-truth/bfsi-bench
Items	167
Languages	English
Split	test
License	CC BY 4.0
Site	ground-truth.in

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Categories

Code	Category	Items
BFSI-JUR	Jurisdiction-Aware Compliance	67
BFSI-NUM	Numerical Reasoning	46
BFSI-TMP	Temporal Logic	24
BFSI-ADV	Red-Team Evasion	30

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Schema

Field	Description
id	Stable public id (bfsi-jur-001, bfsi-num-001, …)
category	Category name
category_code	Short code (BFSI-JUR, BFSI-NUM, BFSI-TMP, or BFSI-ADV)
query	The question / user prompt
gold_answer	The verified correct answer
sources	Source lines used to check the answer (Title | https://…, a bare URL, or a short note)
evidence	JSON list of supporting quotes (see below). Full source documents are not included yet.

Each evidence item looks like:

Field	Description
url	Official source URL, or null for note-only evidence
title	Short source title
quote	Tight supporting span (from verification highlights when available)
context	Broader retrieved passage around the quote
kind	source when a URL is present, otherwise note

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Usage

import json
from datasets import load_dataset

ds = load_dataset("ground-truth/bfsi-bench")
row = ds["test"][0]
print(row["category_code"], row["query"])
print(row["gold_answer"])
print(row["sources"])

evidence = json.loads(row["evidence"])
for item in evidence:
    print(item["kind"], item.get("url"), item["quote"][:200])

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License

This dataset is released under CC BY 4.0. It is meant for evaluating language models on Indian BFSI questions.

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Citation

@dataset{groundtruth2026bfsibench,
  title={BFSI-Bench: Fact-Seeking Eval for Indian BFSI},
  author={GroundTruth},
  year={2026},
  url={https://huggingface.co/datasets/ground-truth/bfsi-bench},
  license={CC-BY-4.0}
}

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Contact

We plan to expand this into a continuous evaluation benchmark that stays up to date as Indian BFSI regulations evolve, while adding new evaluation categories such as multilingual capabilities, groundedness, and false-presupposition testing.

Building evaluations for Indian BFSI, or interested in early access to upcoming GroundTruth datasets? Reach out at miroojin@ground-truth.in or visit ground-truth.in.