Fraud Detection Synthetic Dataset

Dataset Description

This is a synthetic dataset for fraud detection created for the XNL LLM Task 3 challenge. It contains transaction data with labeled fraud cases.

Dataset Summary

Number of transactions: 34767
Fraud rate: 10.19%
Generated using the Synthetic Data Generator tool

Data Fields

transaction_id: Unique identifier for each transaction
user_id: User who made the transaction
timestamp: When the transaction occurred
amount: Transaction amount
merchant: Where the transaction occurred
description: Text description of the transaction
transaction_type: Type of transaction (purchase, subscription, etc.)
device: Device used for the transaction
ip_address: IP address (for online transactions)
location: Geographic location
is_fraud: Target variable - indicates if the transaction is fraudulent (1) or legitimate (0)

Additional Information

This dataset was generated using a synthetic data generator that creates realistic transaction patterns with embedded fraud signals. The data can be used for training and testing fraud detection models.

Argilla Integration

This dataset is also available on Argilla as fraud-detection-transactions for interactive exploration and labeling.