datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Cifer-Fraud-Detection-Dataset-AF
📊 Cifer Fraud Detection Dataset
🧠 Overview
The Cifer-Fraud-Detection-Dataset-AF is a high-fidelity, fully synthetic dataset created to support the development and benchmarking of privacy-preserving, federated, and decentralized machine learning systems in financial fraud detection.
This dataset draws structural inspiration from the PaySim simulator, which was built using aggregated mobile money transaction data from a real financial provider operating in 14+ countries.… See the full description on the dataset page: https://huggingface.co/datasets/CiferAI/Cifer-Fraud-Detection-Dataset-AF.ieee-fraud-detection-pipeline-features
IEEE-CIS Fraud Detection — Model-Ready Feature Dataset
Dataset Summary
This dataset contains 590,540 financial transactions from the IEEE-CIS Fraud Detection competition, processed through a production-grade data pipeline into a clean, labeled, model-ready feature table.
The pipeline adds 16 engineered features on top of the original IEEE-CIS columns — including card-level velocity, email domain risk rates, and amount anomaly ratios — ready for direct use in fraud… See the full description on the dataset page: https://huggingface.co/datasets/Kshitijbhatt1998/ieee-fraud-detection-pipeline-features.fraudshield-10m
FraudShield AI: 10M Synthetic Fraud & Abuse Dataset
This dataset contains 10,000,000 synthetic signup events and 10,000,000 synthetic payment events modeled after enterprise fintech trust and anti-abuse systems.
Dataset Structure
signup/: Features for Graph Neural Network (GraphSAGE) signup trust scoring (train: 90%, test: 10%).
payment/: Features for multi-class LightGBM payment abuse classification (train: 90%, test: 10%).
Quickstart
from… See the full description on the dataset page: https://huggingface.co/datasets/vicky1428/fraudshield-10m.Creditcard-fraud-detection
Credit Card Fraud Detection
This dataset was downloaded from https://www.kaggle.com/datasets/mlg-ulb/creditcardfraud/data adn uploaded for educational purposes.
Nigerian-Financial-Transactions-and-Fraud-Detection-Dataset
Nigerian Financial Transactions and Fraud Detection Dataset | Africa (Electric Sheep Africa metadata inventory)
Size category: 1M<n<10M - Formats: csv - Sector: economics_finance - Engineered by Electric Sheep Africa
TL;DR
This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.
What This Dataset… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/Nigerian-Financial-Transactions-and-Fraud-Detection-Dataset.european_credit_card_fraud_datasetethereum_fraud_dataset_by_activity
🕸 Ethereum Address Behavior Dataset — GNN + LSTM (Fraud Detection)
This dataset is designed for fraud detection on Ethereum addresses using a dual-modality approach:
Graph Neural Networks (GNN): transaction graph structure.
Recurrent Models (LSTM/Transformers): time-series of address features.
The dataset is built from:
Ethereum public BigQuery dataset (bigquery-public-data.crypto_ethereum.transactions).
Etherscan labels + custom scam labels.
Balanced address list of ~115k… See the full description on the dataset page: https://huggingface.co/datasets/fesevu/ethereum_fraud_dataset_by_activity.chess-fraud
ChessFraud
ChessFraud is a tabular benchmark for cheating detection in online chess. It
accompanies the KDD 2026 Datasets and Benchmarks Track paper ChessFraud:
Exploring the Capabilities of Human-Aligned Models for Cheating Detection in
Online Chess.
The two configurations serve complementary roles. ChessFraud supports
evaluation against cheating observed under a controlled assistance protocol.
ChessFraud-Synth supports training and analysis using alternatives produced
by… See the full description on the dataset page: https://huggingface.co/datasets/artemlepin/chess-fraud.fed-fraud-paysim-banks
Dataset Card for fed-fraud-paysim-banks
This dataset originates from purulalwani/Synthetic-Financial-Datasets-For-Fraud-Detection, a Hugging Face version of the PaySim-style synthetic mobile-money fraud detection dataset.
This derived version creates a federated, bank-partitioned fraud detection dataset by assigning originator accounts to one of five banks and preserving each account within a single bank partition.
Dataset Details
Dataset Description… See the full description on the dataset page: https://huggingface.co/datasets/flwrlabs/fed-fraud-paysim-banks.Cifer-Fraud-Detection-Dataset-AF
📊 Cifer Fraud Detection Dataset
🧠 Overview
The Cifer-Fraud-Detection-Dataset-AF is a high-fidelity, fully synthetic dataset created to support the development and benchmarking of privacy-preserving, federated, and decentralized machine learning systems in financial fraud detection.
This dataset draws structural inspiration from the PaySim simulator, which was built using aggregated mobile money transaction data from a real financial provider operating in 14+ countries.… See the full description on the dataset page: https://huggingface.co/datasets/nithi060488/Cifer-Fraud-Detection-Dataset-AF.travel-fraud-graphs
TravelFraudBench (TFG)
The first publicly available labeled heterogeneous graph benchmark for GNN-based fraud ring detection in travel networks.
Paper
Dataset Structure
This dataset contains heterogeneous graph data split into 20 named configurations — one per node type and one per edge type — each with small, medium, and large splits.
Loading a specific node or edge table
from datasets import load_dataset
# Load user nodes (medium scale)
users =… See the full description on the dataset page: https://huggingface.co/datasets/bsajja7/travel-fraud-graphs.credit-card-fraud-detection
Credit Card Fraud Detection – Processed Dataset
This dataset contains preprocessed credit card transaction data prepared for fraud detection tasks.
Data Description
The dataset is derived from anonymized transaction records and includes numerical features (V1–V28), transaction amount, and time-based information.
Preprocessing Steps
Feature scaling and normalization
Handling class imbalance
Feature selection based on correlation analysis
Removal of irrelevant… See the full description on the dataset page: https://huggingface.co/datasets/jyunyilin/credit-card-fraud-detection.Synthetic-Financial-Datasets-For-Fraud-DetectionCifer-Fraud-Detection-Dataset-AF
📊 Cifer Fraud Detection Dataset
🧠 Overview
The Cifer-Fraud-Detection-Dataset-AF is a high-fidelity, fully synthetic dataset created to support the development and benchmarking of privacy-preserving, federated, and decentralized machine learning systems in financial fraud detection.
This dataset draws structural inspiration from the PaySim simulator, which was built using aggregated mobile money transaction data from a real financial provider operating in 14+ countries.… See the full description on the dataset page: https://huggingface.co/datasets/Durgesh111/Cifer-Fraud-Detection-Dataset-AF.credit-card-fraud-curated
credit-card-fraud-detector — Curated dataset
Versión curada del dataset alenc123/credit-card-fraud
con feature engineering aplicado y splits estratificados train/test. Listo para
benchmarking de clasificadores binarios sobre fraude.
Composición
Train: 1,037,340 filas
Test: 259,335 filas
Features finales: 30
Tasa de fraude: ~0.579% (estratificada en ambos splits)
Target: is_fraud ∈ {0, 1}
Preprocesamiento aplicado
Drop de columnas sin señal: Unnamed: 0… See the full description on the dataset page: https://huggingface.co/datasets/gusdelact/credit-card-fraud-curated.fraud-detection-eda
PaySim Financial Fraud Detection — EDA & Dataset Analysis
Presentation Video
Dataset Overview
This project analyzes the PaySim Financial Fraud Detection dataset from Kaggle (source: chitwanmanchanda/fraudulent-transactions-data). The dataset contains simulated mobile money transactions with fraud labels, representing 100,000 randomly sampled transactions (random_state=42) from the original 6,362,620 rows.
Key characteristics:
Total records: 100,000… See the full description on the dataset page: https://huggingface.co/datasets/MichaelGelshtein/fraud-detection-eda.ethereum_fraud_detectioncredit_card_fraud_transactionscc_fraud_detection_datasetafrica-synth-insurance-fraud-detection-all
African Insurance Fraud Detection | Africa (Electric Sheep Africa metadata inventory)
Size category: 100K<n<1M - Formats: csv - Sector: culture_language - Engineered by Electric Sheep Africa
TL;DR
This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.
What This Dataset Covers
Public datasets… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-synth-insurance-fraud-detection-all.crypto-holder-concentration
FraudCoins on-chain holder-concentration dataset
Daily on-chain measurements of top-10 holder concentration for cryptocurrency
tokens, plus contract-permission data — published under CC BY 4.0 and archived
with a DOI.
DOI: 10.5281/zenodo.22494421 ·
Docs: https://fraudcoins.com/data/ ·
Live API: https://fraudcoins.com/dataset/v1/ (no key, CORS enabled)
What makes it different
A raw "top 10 holders hold X%" figure counts whatever the ten largest addresses
happen to… See the full description on the dataset page: https://huggingface.co/datasets/Fraudcoins/crypto-holder-concentration.Nigerian-Financial-Transactions-and-Fraud-Detection-Dataset
Dataset Card for GLUE
Dataset Summary
GLUE, the General Language Understanding Evaluation benchmark (https://gluebenchmark.com/) is a collection of resources for training, evaluating, and analyzing natural language understanding systems.
Supported Tasks and Leaderboards
The leaderboard for the GLUE benchmark can be found at this address. It comprises the following tasks:
ax
A manually-curated evaluation dataset for fine-grained analysis of system… See the full description on the dataset page: https://huggingface.co/datasets/demola2/Nigerian-Financial-Transactions-and-Fraud-Detection-Dataset.synthetic-fraud-detectionlead-ai-fraud-detection-dataset-v2
Lead.AI Fraud Detection Dataset v2 (Research-Grade)
Dataset Description
This is the second version (v2) of the synthetic fraud detection dataset generated for Lead.AI. This version is significantly upgraded to be research-grade, production-ready, and optimized for Trustworthy AI applications, particularly focusing on Explainable AI (XAI) methods like SHAP and LIME. It simulates realistic transaction data with a controlled class imbalance (1-2% fraud rate).
Why v2?… See the full description on the dataset page: https://huggingface.co/datasets/arun-gharami/lead-ai-fraud-detection-dataset-v2.Machine-Learning-Credit-Card-Fraud-Detection-Projectbank-transaction-fraudfraud_detectionfraud-detection-underserved-20k
Underserved Financial Fraud Detection Dataset
Created with Adaptive Data by Adaption | CC BY 4.0 | 20,000 records | 8 languages | 390 reasoning traces
The first open-source fraud dataset built specifically around populations that PaySim, Sparkov, and IEEE-CIS have never modeled — immigrant remittance senders, gig workers, unbanked cash users, and ITIN-based entrepreneurs. These communities are disproportionately targeted by fraud. This dataset fills that gap.
This dataset was… See the full description on the dataset page: https://huggingface.co/datasets/Nachammai41/fraud-detection-underserved-20k.creditcard-fraud-datasetlead-ai-fraud-detection-dataset
📊 Lead.AI Fraud Detection Dataset
5,000-Row Synthetic Tabular Benchmark — Ready to Train, Ready to Publish
Published by Lead.AI Labs · Author: Arun Kumar Gharami
What This Dataset Is For
A clean, Parquet-formatted, immediately loadable synthetic fraud detection dataset built
for researchers, ML engineers, and course instructors who need realistic tabular financial
data without the legal complexity of real transaction data.
Use it to:
Build and benchmark… See the full description on the dataset page: https://huggingface.co/datasets/arun-gharami/lead-ai-fraud-detection-dataset.