{"url":"/dataset/ieee-cis-fraud-detection-1","name":"IEEE CIS Fraud Detection","full_name":"IEEE CIS Fraud Detection (Vesta)","description_markdown":"The Vesta dataset was released for use in the IEEE CIS Fraud Detection competition. It contains 590,540 card transactions, 20,663 of which are fraudulent (3.5%). Each\r\ntransaction has 431 features (400 numerical, 31 categorical), along with the relative\r\ntimestamp and a label of whether it was fraudulent or legitimate. For anonymization\r\npurposes, the names of the identity features have been masked, along with the names of\r\nthe extra features engineered by Vesta.","description_withheld":null,"homepage":"https://www.kaggle.com/competitions/ieee-fraud-detection/","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[],"tasks":[],"languages":[],"variants":["IEEE CIS Fraud Detection"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}