--- license: cc-by-nc-sa-4.0 task_categories: - tabular-classification tags: - anti-money-laundering - aml - fraud-detection - graph - synthetic - finance - transactions pretty_name: QM Synthetic AML Transfer Network configs: - config_name: transactions data_files: transactions_sample.csv default: true - config_name: accounts data_files: accounts.csv - config_name: cases data_files: cases.csv --- # QM Synthetic AML Transfer Network - Free Sample **Buy the full commercial edition: $5 USD -> [Polar checkout, instant download](https://buy.polar.sh/polar_cl_HnkK7xRcMaBfwFmfVUYNijc7MXsqYg2A3viVi2I5BcY)** This free sample is non-commercial (CC BY-NC-SA 4.0). The paid full edition has a commercial licence. ## Summary Synthetic bank transfers with labelled money-laundering cases, for anti-money-laundering (AML) model development, graph ML and transaction-monitoring rule testing; the paid full edition can be used commercially. - Best for: AML model prototyping, GNN / graph-motif research, testing monitoring rules, training and demos without customer data - Not for: regulatory model validation or estimating real laundering prevalence ## Quick start ```python from datasets import load_dataset ds = load_dataset("quailrobot/aml-v1-sample", split="train") # main table: transactions_sample.csv # pandas alternative: pd.read_csv("hf://datasets/quailrobot/aml-v1-sample/transactions_sample.csv") ``` ## Facts - Task: tabular / graph binary classification (laundering detection) + typology evaluation - Labels: is_laundering (0/1); typology = fan_in_smurfing, fan_out, cycle, layering_chain, scatter_gather; case_id - Full edition size: 4,746,819 transfers, 100,000 accounts, 180 days, 200 laundering cases - Free sample size: 567,302 transfers = first 20 days (transactions_sample.csv); roles and cases only for laundering seen in that window (22 cases) - Format: full: Parquet (transactions) + CSV (accounts, cases); sample: CSV - What's included (full edition): transactions.parquet, accounts.csv, cases.csv, stats.json, benchmark.json, bench_aml.py, README.md, LICENSE.txt - Price: $5 USD; checkout may display the equivalent in your local currency - Buy URL (primary): https://buy.polar.sh/polar_cl_HnkK7xRcMaBfwFmfVUYNijc7MXsqYg2A3viVi2I5BcY - Licence (full edition): LicenseRef-QuailModel-Commercial (commercial use allowed, no resale of the data) - Licence (free sample): CC-BY-NC-SA-4.0 - Validation: Our own test on the full edition (time split, train first 70 % of days): class-balanced gradient boosting on 11 flat per-transaction features ROC-AUC 0.980, PR-AUC 0.157 (benchmark.json + script included). Graph-aware methods should do better. - Data source: 100% synthetic, generated by QuailModel with AI assistance (generator code written with an AI model) - Catalog (all QuailModel datasets, catalog.json, llms.txt): https://quailrobot-quailmodel.static.hf.space - Last updated: 2026-10-10 ## Validation Our own test on the full edition (time split, train first 70 % of days): class-balanced gradient boosting on 11 flat per-transaction features ROC-AUC 0.980, PR-AUC 0.157 (benchmark.json + script included). Graph-aware methods should do better. ## Price & licence - Full edition: $5 USD. One-time payment, instant download after checkout: https://buy.polar.sh/polar_cl_HnkK7xRcMaBfwFmfVUYNijc7MXsqYg2A3viVi2I5BcY - QuailModel Commercial Dataset Licence (SPDX: LicenseRef-QuailModel-Commercial): you may train, evaluate and ship models, including in commercial products. You may not resell or redistribute the dataset itself. - Free sample (this page): CC BY-NC-SA 4.0 - free for non-commercial use. ## Limitations - 100% synthetic: not validated against real bank data - check on your own data before production. - Typologies are simulated patterns; real laundering is more varied. ## Custom dataset of YOUR object ($249) **Need data of YOUR object? Custom Object-Detection Dataset of Your Object (2,000 images), $249 USD -> [order on Polar](https://buy.polar.sh/polar_cl_AQu6LzRtqiQmKPlgPt0zePBtvWjJI4vULeFMQ4NLHH9)** - Note: this is an image / object-detection service (not tabular data). - What you get: 2,000 labelled photoreal synthetic images (640x640 JPEG) of your own object or scenario (product, part, tool, drone, package, defect...), up to 3 classes, YOLO bounding boxes + data.yaml, train/val/test split, quality report - Licence: commercial use allowed - Price: $249 USD one-time; one round of adjustments included - Delivery: typically 3-5 business days after we receive your reference photos + rough dimensions - Optional sim-to-real test: send ~200 of your own labelled real images and we report how much the synthetic data improves a detector on them - Refund: full refund if we cannot deliver your request (14-day refund policy) - Limits: only objects you own or are allowed to use; no weapons or anything meant to harm people; no copied third-party 3D assets - Order URL: https://buy.polar.sh/polar_cl_AQu6LzRtqiQmKPlgPt0zePBtvWjJI4vULeFMQ4NLHH9 - Details + contact: https://quailrobot-quailmodel.static.hf.space **This free sample:** 461,111 transfers = first 20 days (transactions_sample.csv); roles and cases only for laundering seen in that window. **Full commercial edition:** 3,795,865 transfers, 100,000 accounts, 180 days, 200 laundering cases (zip 67 MB). Fully synthetic data; summary, facts, validation and limitations are in the block above. ## Files | file | content | |---|---| | transactions | transaction_id, amount, timestamp, channel, is_laundering, typology, case_id, src_account, dst_account, currency | | accounts.csv | account_id, type, bank, country, opened_days_ago, laundering_role | | cases.csv | case_id, typology, n_tx | | benchmark.json, bench_aml.py | reproducible baseline (full edition) | ## How it was made Produced by QuailModel's own simulator, including legitimate activity alongside the labelled patterns. Labels are exact, because they are known by construction. ## Credits No third-party data was used. ## Licence Sample edition: CC BY-NC-SA 4.0 (non-commercial). The full commercial edition is sold by QuailModel (see the buy link). ## Disclosure Generated by QuailModel with AI assistance (generator code written with an AI model); all data is synthetic / computer-generated. Validate on your own real data before production use.