Datasets:

VynFi
/

vynfi-aml-100k

license: apache-2.0
task_categories:
  - tabular-classification
tags:
  - synthetic
  - financial-data
  - vynfi
  - aml
  - banking
  - fraud-detection
size_categories:
  - 100K<n<1M

VynFi AML: 748K Banking Transactions with AML Labels

748,869 synthetic banking transactions. Financial services sector, 5 companies, 6 monthly periods. 59 columns including 14 pre-computed velocity features.

411 suspicious transactions (0.05%)
37,419 false positives (5% injection rate)
11 transaction channels (ACH, ATM, card, cash, check, mobile, online, P2P, SWIFT, wire)
Counterparty details, velocity windows (1h/24h/7d/30d), amount z-scores

The suspicious rate is low by design. Production AML systems see comparable rates. The false-positive injection provides realistic noise for threshold calibration.

Limitations

Labels are generated, not from real SARs. Typology patterns are rule-based, not learned from case data.
Velocity features are computed per-account over the synthetic timeline. They reflect the generation model's temporal logic, not real transaction behavior.
The 100K row parameter produced 748K banking transactions due to the engine's expansion factor. This is a property of the generation, not a data error.

Citation

@dataset{ivertowski_vynfi_aml_2026,
  title     = {VynFi AML: 748K Banking Transactions with AML Labels},
  author    = {Michael Ivertowski},
  year      = {2026},
  url       = {https://huggingface.co/datasets/VynFi/vynfi-aml-100k},
  note      = {Generated with VynFi (https://vynfi.com)}
}

License: Apache 2.0. Entirely synthetic.