Datasets:

TheFinAI
/

en-ccfraud

pretty_name: CALM · ccFraud (fraud detection)
license: other
license_name: public-source
language:
  - en
task_categories:
  - text-classification
size_categories:
  - 10K<n<100K
source_datasets:
  - extended
tags:
  - finance
  - benchmark
  - thefinai
  - calm
  - flare
extra_gated_heading: Request access to CALM · ccFraud (fraud detection)
extra_gated_description: >-
  This CALM task is released by The Fin AI for research. Access is granted
  automatically after you complete this short form.
extra_gated_button_content: Agree and access
extra_gated_prompt: >-
  By accessing this dataset you agree to the license of the original source
  (Public) and to cite the CALM paper and the original dataset in any resulting
  publication.
extra_gated_fields:
  Full name: text
  Affiliation: text
  Country: country
  Intended use:
    type: select
    options:
      - Research
      - Education
      - Commercial evaluation
      - Other
  I agree to the terms above and will cite the papers: checkbox

CALM · ccFraud (fraud detection)

📄 Paper · 💻 Code · 🌐 The Fin AI

Part of CALM — Empowering Many, Biasing a Few: Generalist Credit Scoring through Large Language Models (arXiv:2310.00566).


Task	fraud detection
Original dataset	ccFraud
Evaluation metric	Accuracy, MCC, F1, Miss
Source license	Public
Language	en

Quick Start

from datasets import load_dataset

ds = load_dataset("TheFinAI/en-ccfraud", split="test")
print(ds[0])

Example prompt

Detect the credit card fraud with the following financial profile. Respond with only 'good' or 'bad', and do not provide any additional information. For instance, 'The client is a female, the state number is 25, the number of cards is 1, the credit balance is 7000, the number of transactions is 16, the number of international transactions is 0, the credit limit is 6.' should be classified as 'good…

Dataset Structure

Split	Rows
`train`	7,339
`validation`	1,048
`test`	2,098

Field	Description
`id`	Example id
`query`	Full instruction prompt given to the model
`answer`	Gold answer / label text
`choices`	Label space
`gold`	Index of the gold label in `choices`
`text`	Raw input text (without instruction)

License

The paper lists the original data as publicly available without a specific license (CALM paper, Table 1); refer to the original source for its terms.

Citation

Please cite CALM and the original dataset (ccFraud):

@misc{feng2024empoweringmanybiasingfew,
      title={Empowering Many, Biasing a Few: Generalist Credit Scoring through Large Language Models},
      author={Duanyu Feng and Yongfu Dai and Jimin Huang and Yifang Zhang and Qianqian Xie and Weiguang Han and Zhengyu Chen and Alejandro Lopez-Lira and Hao Wang},
      year={2024},
      eprint={2310.00566},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2310.00566},
}