Fillings
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1.63k
5.71M
Fraud
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"item 14 principal accounting fees services material included 2014 proxy statement headings audit fe(...TRUNCATED)
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"item 14 exhibits financial statements schedules reports form 8k afinancial statements schedules 1 f(...TRUNCATED)
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"item 14 exhibits financial statement schedules reports form 8k 1 financial statements presentation (...TRUNCATED)
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"item 14 exhibits financial statement schedules reports form 8k exhibits 21 restated agreement plan (...TRUNCATED)
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"item 14 principal accountant fees services information required item incorporated reference informa(...TRUNCATED)
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"item 14 principal accountant fees services information appearing caption “independent public acco(...TRUNCATED)
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"item 14 exhibits financial statement schedules reports form 8k financial statements financial state(...TRUNCATED)
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Dataset Card for Financial Fraud Labeled Dataset

Dataset Details

This dataset collects financial filings from various companies submitted to the U.S. Securities and Exchange Commission (SEC). The dataset consists of 85 companies involved in fraudulent cases and an equal number of companies not involved in fraudulent activities. The Fillings column includes information such as the company's MD&A, and financial statement over the years the company stated on the SEC website.

This dataset was used for research in detecting financial fraud using multiple LLMs and traditional machine-learning models.

  • Curated by: Amit Kedia
  • Language(s) (NLP): English
  • License: Apache 2.0

Dataset Sources

Direct Use

Code to Directly use the dataset:

from datasets import load_dataset

dataset = load_dataset("amitkedia/Financial-Fraud-Dataset")

Out-of-Scope Use

There are some limitations of the dataset:

  1. This dataset is designed for acedemic research
  2. The text needs to be cleaned for further process
  3. The dataset does not cover all the fradulent cases and are limited to Securities and Exchange Commision of USA (SEC) that means the fradulent and non fradulent cases are the companies of USA

Dataset Structure

For the structure of the dataset look into the dataset viewer.

Dataset Creation

Check out the Thesis

Curation Rationale

To help the financial industry develop the best model to detect fraudulent activities which can save billions of dollars for government and banks

Data Collection and Processing

Please Refer to the Thesis

Dataset Card Authors

Amit Kedia

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