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arXiv · 2108.04494

Finding NeMo: Fishing in banking networks using network motifs

Xavier Fontes·David Aparício·Maria Inês Silva·Beatriz Malveiro·João Tiago Ascensão·Pedro Bizarro
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Abstract

Banking fraud causes billion-dollar losses for banks worldwide. In fraud detection, graphs help understand complex transaction patterns and discovering new fraud schemes. This work explores graph patterns in a real-world transaction dataset by extracting and analyzing its network motifs. Since banking graphs are heterogeneous, we focus on heterogeneous network motifs. Additionally, we propose a novel network randomization process that generates valid banking graphs. From our exploratory analysis, we conclude that network motifs extract insightful and interpretable patterns.

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Xavier Fontes, David Aparício, Maria Inês Silva, Beatriz Malveiro, João Tiago Ascensão, Pedro Bizarro. 2021-08-10. Finding NeMo: Fishing in banking networks using network motifs. https://arxiv.org/abs/2108.04494

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