Bitcoin Illicit Transaction Dataset for AML Model Training

A dataset for training models to identify illicit Bitcoin transactions. The data is hosted on Kaggle and is intended to empower anti-money laundering (AML) efforts. The author, organization, and specific data characteristics are unknown.

Use Cases

• Train binary classifiers to detect illicit transactions based on transaction features.
• Benchmark AML detection algorithms using cryptocurrency data.
• Analyze patterns associated with illicit Bitcoin activity mentioned in the description.

Strengths

• The dataset has a clear, focused purpose for anti-money laundering applications.
• It is hosted on Kaggle, a platform with established data sharing and community features.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

Kaggle