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xFraud: Explainable Fraud Transaction Detection

Summary: Detector uses a heterogeneous graph neural network to predict transaction legitimacy from heterogeneous entities. Explainer provides human-understandable graph explanations; scalable to 1.1B nodes and 3.7B edges, improving metrics over baselines. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
13107
Venue
VLDB
Year
2022
Pagerank
6.577136e-05
Overall Rank
4,666 | 67.99%
DOI
10.14778/3494124.3494128

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{rao_vldb22,
        title = {{xFraud: Explainable Fraud Transaction Detection}},
        author = {Rao, Susie Xi and Zhang, Shuai and Han, Zhichao and Zhang, Zitao and Min, Wei and Chen, Zhiyao and Shan, Yinan and Zhao, Yang and Zhang, Ce},
        journal = {PVLDB},
        series = {{VLDB} '22},
        volume = {15},
        number = {3},
        pages = {427--436},
        doi = {10.14778/3494124.3494128},
        url = {https://doi.org/10.14778/3494124.3494128},
        year = {2022}
}

Incoming Citations (Sorted by Pagerank)

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Outgoing Citations (Sorted by Pagerank)

Showing 2 of 2 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
3,203 TitAnt: Online Real-time Transaction Fraud Detection in Ant Financial 2019 VLDB 7.6402128e-05
4,964 ZooBP: Belief Propagation for Heterogeneous Networks 2017 VLDB 6.4251416e-05
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