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Fraud Detection datasets
archive 2025-07-28
12 datasets carry the task tag "Fraud Detection" (the task itself: Fraud Detection), ordered by the archive's paper count. Page 1 of 1: 12 shown of 12. Facet routes are this site's own (the archive records the tag string, not a page).
The archive holds 12,214 dataset rows; 12,172 are listed. 6 are withheld from every listing and count here as vandalised before snapshot (6 with contact-centre spam in the title, 0 with a spam description on a row that has no homepage, no paper and no papers counted; none with more than 1 paper, 0 with a benchmark), listed in withheld.json; 1 listed row carries a vandalised description, withheld on its page. This gate never withholds a row with a homepage or a paper that resolves, and a clean description; the content rules below withhold a row whose name is spam whatever else it carries. The gate is a phrase list: these are the rows it caught, not a claim that the rest is clean. Before that gate, the site's content rules withhold 36 more rows (invite-code, gambling, travel-booking, contact-centre and similar spam in the name or on a row with nothing real behind it); they have no page and are listed in withheld.json.
Filter 51 task tags shown of 3,717, by dataset count; the full filter by modality, task and language is on /datasets
Fraud Detection datasets 1–12 of 12
The Yelp Dataset is a valuable resource for academic research, teaching, and learning.
86 papers · 15 benchmarks
Click to add a brief description of the dataset (Markdown and LaTeX enabled).
18 papers · 1 benchmark
Yelp-Fraud (Multi-relational Graph Dataset for Yelp Spam Review Detection)
Yelp-Fraud is a multi-relational graph dataset built upon the Yelp spam review dataset, which can be used in evaluating graph-based node classification, fraud detection, and anomaly detection models.
13 papers · 3 benchmarks
Bank Account Fraud (BAF) is a large-scale, realistic suite of tabular datasets.
10 papers · 12 benchmarks
Amazon-Fraud (Multi-relational Graph Dataset for Amazon Fraudulent Account Detection)
Amazon-Fraud is a multi-relational graph dataset built upon the Amazon review dataset, which can be used in evaluating graph-based node classification, fraud detection, and anomaly detection models.
8 papers · 3 benchmarks
The dataset contains transactions made by credit cards in September 2013 by European cardholders.
8 papers · 2 benchmarks
Money laundering is a multi-billion dollar issue.
4 papers · 0 benchmarks
A new fraud detection dataset FDCompCN for detecting financial statement fraud of companies in China.
2 papers · 1 benchmark
The code to create the dataset is available here.
2 papers · 2 benchmarks
Inpatient claims, Outpatient claims and Beneficiary details of each provider.
1 paper · 1 benchmark
CIDII Dataset (Correct Information and Disinformation about Islamic Issues)
The CIDII dataset is a binary classification, consisting of two classes of correct information and disinformation related to Islamic issues.
0 papers · 0 benchmarks
Can you detect fraud from customer transactions?
0 papers · 0 benchmarks
Paper counts and descriptions are the archive's, frozen 2025-07-28; no citation counts, no stars, no trending. Sorting by "most cited" or "newest" was a live-site feature the archive does not carry.