{"url":"/dataset/baf","name":"BAF","full_name":"Bank Account Fraud","description_markdown":"**Bank Account Fraud (BAF)** is a large-scale, realistic suite of tabular datasets. The suite was generated by applying state-of-the-art tabular data generation techniques on an anonymized, real-world bank account opening fraud detection dataset.\r\n\r\nSource: [Turning the Tables: Biased, Imbalanced, Dynamic Tabular Datasets for ML Evaluation](https://arxiv.org/pdf/2211.13358v1.pdf)","description_withheld":null,"homepage":"https://github.com/feedzai/bank-account-fraud","introduced_date":"2022-11-24","introduced_date_note":null,"introduced_by":{"paper":"/paper/turning-the-tables-biased-imbalanced-dynamic","title":"Turning the Tables: Biased, Imbalanced, Dynamic Tabular Datasets for ML Evaluation","first_author":"Sérgio Jesus","url":null},"license":{"name":"Apache-2.0 license","url":"https://github.com/feedzai/bank-account-fraud/blob/main/LICENSE"},"modalities":[{"name":"Tabular","url":"/datasets/modality/tabular"}],"tasks":[{"name":"Fraud Detection","url":"/task/fraud-detection","datasets_with_task":"/datasets/task/fraud-detection"},{"name":"Fairness","url":"/task/fairness","datasets_with_task":"/datasets/task/fairness"}],"languages":[],"variants":["BAF","BAF – Base","BAF – Variant I","BAF – Variant II","BAF – Variant III","BAF – Variant IV","BAF – Variant V"],"data_loaders":[],"num_papers_in_archive":10,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/fraud-detection-on-baf-base","task":"Fraud Detection","dataset_variant":"BAF – Base","rows":12,"metrics":["Recall @ 1% FPR","Recall @ 5% FPR"],"first_row_in_archive_order":{"model":"LightGBM","paper":"/paper/riff-inducing-rules-for-fraud-detection-from","metrics":{"Recall @ 1% FPR":"25.2%"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/fairness-on-baf-base","task":"Fairness","dataset_variant":"BAF – Base","rows":2,"metrics":["Predictive Equality (age)"],"first_row_in_archive_order":{"model":"1D-CSNN","paper":"/paper/improving-fraud-detection-with-1d","metrics":{"Predictive Equality (age)":"99.86%"},"code_links":[{"title":"DylanPerdigao/Bayesian-Optimization-1D-CSNN","url":"https://github.com/DylanPerdigao/Bayesian-Optimization-1D-CSNN"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/fairness-on-baf-variant-i","task":"Fairness","dataset_variant":"BAF – Variant I","rows":1,"metrics":["Predictive Equality (age)"],"first_row_in_archive_order":{"model":"1D-CSNN","paper":"/paper/exploring-neural-joint-activity-in-spiking","metrics":{"Predictive Equality (age)":"96.87%"},"code_links":[{"title":"DylanPerdigao/Neural-Joint-Activity-in-SNNs","url":"https://github.com/DylanPerdigao/Neural-Joint-Activity-in-SNNs"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/fairness-on-baf-variant-ii","task":"Fairness","dataset_variant":"BAF – Variant II","rows":1,"metrics":["Predictive Equality (age)"],"first_row_in_archive_order":{"model":"1D-CSNN","paper":"/paper/exploring-neural-joint-activity-in-spiking","metrics":{"Predictive Equality (age)":"98.97%"},"code_links":[{"title":"DylanPerdigao/Neural-Joint-Activity-in-SNNs","url":"https://github.com/DylanPerdigao/Neural-Joint-Activity-in-SNNs"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/fairness-on-baf-variant-iii","task":"Fairness","dataset_variant":"BAF – Variant III","rows":1,"metrics":["Predictive Equality (age)"],"first_row_in_archive_order":{"model":"1D-CSNN","paper":"/paper/exploring-neural-joint-activity-in-spiking","metrics":{"Predictive Equality (age)":"98.45%"},"code_links":[{"title":"DylanPerdigao/Neural-Joint-Activity-in-SNNs","url":"https://github.com/DylanPerdigao/Neural-Joint-Activity-in-SNNs"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/fairness-on-baf-variant-iv","task":"Fairness","dataset_variant":"BAF – Variant IV","rows":1,"metrics":["Predictive Equality (age)"],"first_row_in_archive_order":{"model":"1D-CSNN","paper":"/paper/exploring-neural-joint-activity-in-spiking","metrics":{"Predictive Equality (age)":"98.68%"},"code_links":[{"title":"DylanPerdigao/Neural-Joint-Activity-in-SNNs","url":"https://github.com/DylanPerdigao/Neural-Joint-Activity-in-SNNs"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/fairness-on-baf-variant-v","task":"Fairness","dataset_variant":"BAF – Variant V","rows":1,"metrics":["Predictive Equality (age)"],"first_row_in_archive_order":{"model":"1D-CSNN","paper":"/paper/exploring-neural-joint-activity-in-spiking","metrics":{"Predictive Equality (age)":"99.31%"},"code_links":[{"title":"DylanPerdigao/Neural-Joint-Activity-in-SNNs","url":"https://github.com/DylanPerdigao/Neural-Joint-Activity-in-SNNs"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/fraud-detection-on-baf-variant-i","task":"Fraud Detection","dataset_variant":"BAF – Variant I","rows":1,"metrics":["Recall @ 5% FPR"],"first_row_in_archive_order":{"model":"1D-CSNN","paper":"/paper/exploring-neural-joint-activity-in-spiking","metrics":{"Recall @ 5% FPR":"40.71%"},"code_links":[{"title":"DylanPerdigao/Neural-Joint-Activity-in-SNNs","url":"https://github.com/DylanPerdigao/Neural-Joint-Activity-in-SNNs"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/fraud-detection-on-baf-variant-ii","task":"Fraud Detection","dataset_variant":"BAF – Variant II","rows":1,"metrics":["Recall @ 5% FPR"],"first_row_in_archive_order":{"model":"1D-CSNN","paper":"/paper/exploring-neural-joint-activity-in-spiking","metrics":{"Recall @ 5% FPR":"47.08%"},"code_links":[{"title":"DylanPerdigao/Neural-Joint-Activity-in-SNNs","url":"https://github.com/DylanPerdigao/Neural-Joint-Activity-in-SNNs"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/fraud-detection-on-baf-variant-iii","task":"Fraud Detection","dataset_variant":"BAF – Variant III","rows":1,"metrics":["Recall @ 5% FPR"],"first_row_in_archive_order":{"model":"1D-CSNN","paper":"/paper/exploring-neural-joint-activity-in-spiking","metrics":{"Recall @ 5% FPR":"41.83%"},"code_links":[{"title":"DylanPerdigao/Neural-Joint-Activity-in-SNNs","url":"https://github.com/DylanPerdigao/Neural-Joint-Activity-in-SNNs"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/fraud-detection-on-baf-variant-iv","task":"Fraud Detection","dataset_variant":"BAF – Variant IV","rows":1,"metrics":["Recall @ 5% FPR"],"first_row_in_archive_order":{"model":"1D-CSNN","paper":"/paper/exploring-neural-joint-activity-in-spiking","metrics":{"Recall @ 5% FPR":"35.54%"},"code_links":[{"title":"DylanPerdigao/Neural-Joint-Activity-in-SNNs","url":"https://github.com/DylanPerdigao/Neural-Joint-Activity-in-SNNs"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/fraud-detection-on-baf-variant-v","task":"Fraud Detection","dataset_variant":"BAF – Variant V","rows":1,"metrics":["Recall @ 5% FPR"],"first_row_in_archive_order":{"model":"1D-CSNN","paper":"/paper/exploring-neural-joint-activity-in-spiking","metrics":{"Recall @ 5% FPR":"34.96%"},"code_links":[{"title":"DylanPerdigao/Neural-Joint-Activity-in-SNNs","url":"https://github.com/DylanPerdigao/Neural-Joint-Activity-in-SNNs"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/exploring-neural-joint-activity-in-spiking","title":"Exploring Neural Joint Activity in Spiking Neural Networks for Fraud Detection","date":"2024-11-17","rows_on_this_dataset":13,"code_links":1,"syntology":null},{"paper":"/paper/improving-fraud-detection-with-1d","title":"Improving Fraud Detection with 1D-Convolutional Spiking Neural Networks Through Bayesian Optimization","date":"2024-11-16","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/riff-inducing-rules-for-fraud-detection-from","title":"RIFF: Inducing Rules for Fraud Detection from Decision Trees","date":"2024-08-23","rows_on_this_dataset":6,"code_links":0,"syntology":null},{"paper":"/paper/decoupling-decision-making-in-fraud","title":"Decoupling Decision-Making in Fraud Prevention through Classifier Calibration for Business Logic Action","date":"2024-01-10","rows_on_this_dataset":3,"code_links":0,"syntology":null}],"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."}