DerwenAI/kleptosyn
Synthetic data generation for investigative graphs based on patterns of bad-actor tradecraft.
This project helps financial crime analysts and investigators generate realistic synthetic data to practice identifying complex fraud networks. It takes real-world data about entities and their relationships (like company ownership) and information from known financial crime cases. It then generates new, large datasets of transactions and entities, including both legitimate activity and patterns of bad-actor tradecraft, which can be used to test detection systems or train new analysts.
Use this if you need to create diverse, synthetic datasets that mimic real-world financial fraud scenarios for training, testing, or research without using sensitive actual data.
Not ideal if you are looking for a tool to directly analyze live financial transactions or identify fraud in real-time production systems.
Stars
8
Forks
—
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Jan 20, 2026
Commits (30d)
0
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