A minimal example of an ERKG graph used in anti-fraud (AML)
The code uses Python versions 3.11 through 3.13, and gets validated on these through continuous integration.
The following must be downloaded and installed to run this tutorial:
- Git https://git-scm.com/install/
- Python 3.11-3.13 https://www.python.org/downloads/release/python-3139/
- Poetry https://python-poetry.org/docs/
To get started, use git to clone the repo, then connect into the
repo directory and use poetry to install the Python dependencies:
git clone https://github.com/DerwenAI/min_aml.git
cd min_aml
poetry updateThen run JupyterLab and navigate to the demo.ipynmb notebook to view
the datasets:
poetry run jupyter labLicense and Copyright
Source code for this repository plus its logo, documentation, and examples have an MIT license which is succinct and simplifies use in commercial applications.
All materials herein are Copyright © 2026 Senzing, Inc.