no code implementations • 13 Feb 2024 • Jovan Blanuša, Maximo Cravero Baraja, Andreea Anghel, Luc von Niederhäusern, Erik Altman, Haris Pozidis, Kubilay Atasu
In this paper, we present "Graph Feature Preprocessor", a software library for detecting typical money laundering and fraud patterns in financial transaction graphs in real time.
1 code implementation • NeurIPS 2023 • Erik Altman, Jovan Blanuša, Luc von Niederhäusern, Béni Egressy, Andreea Anghel, Kubilay Atasu
To this end, this paper contributes a synthetic financial transaction dataset generator and a set of synthetically generated AML (Anti-Money Laundering) datasets.
no code implementations • 20 Jun 2023 • Béni Egressy, Luc von Niederhäusern, Jovan Blanusa, Erik Altman, Roger Wattenhofer, Kubilay Atasu
This paper analyses a set of simple adaptations that transform standard message-passing Graph Neural Networks (GNN) into provably powerful directed multigraph neural networks.