HyperMining: Explainable Anti-Money Laundering

In this project, we aim to develop an innovative method for detecting money laundering activities, based on advanced AI techniques using hypergraph representations and process mining. This approach provides a coherent view of the transactions involved, can handle the complexity of the data, and remains interpretable for domain experts, enabling them to substantiate their analyses and decisions.

  • PhD Student: Fatemeh Gholamzadeh Nasrabadi
  • Supervisors: Marcel Worring (IvI), Michael Werner (ABS)
  • External Partner: Transaction Monitoring Netherlands

 

Cases

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