Modeling Users' Behavior Sequences with Hierarchical Explainable Network for Cross-domain Fraud Detection. (arXiv:2201.01004v1 [cs.LG])

With the explosive growth of the e-commerce industry, detecting online
transaction fraud in real-world applications has become increasingly important
to the development of e-commerce platforms. The sequential behavior history of
users provides useful information in differentiating fraudulent payments from
regular ones. Recently, some approaches have been proposed to solve this
sequence-based fraud detection problem. However, these methods usually suffer
from two problems: the prediction results are difficult to explain and the
exploitation of the internal information of behaviors is insufficient. …

arxiv detection fraud fraud detection modeling network