Datasets:

quailrobot
/

aml-v1-sample

---
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

<!-- qm-buy:start -->
**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
<!-- qm-buy:end -->
**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.

	---
	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

	<!-- qm-buy:start -->
	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
	<!-- qm-buy:end -->

	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.