Fraud Detection

Fraud Detection is a vital topic that applies to many industries including the financial sectors, banking, government agencies, insurance, and law enforcement, and more. Fraud endeavors have detected a radical rise in current years, creating this topic more critical than ever. Despite struggles on the part of the troubled organizations, hundreds of millions of dollars are wasted to fraud each year. Because nearly a few samples confirm fraud in a vast community, locating these can be complex. Data mining and statistics help to predict and immediately distinguish fraud and take immediate action to minimize costs.

Source: Applying support vector data description for fraud detection

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 476–500 of 547 papers

Title	Date	Tasks	Status
Bayesian Stress Testing of Models in a Classification Hierarchy	May 25, 2020	BIG-bench Machine LearningClassification	CodeCode Available
Modeling Heterogeneous Statistical Patterns in High-dimensional Data by Adversarial Distributions: An Unsupervised Generative Framework	Dec 15, 2020	Anomaly DetectionFraud Detection	CodeCode Available
Financial Fraud Detection with Entropy Computing	Mar 14, 2025	Fraud Detection	CodeCode Available
Transferable Adversarial Robustness for Categorical Data via Universal Robust Embeddings	Jun 6, 2023	Adversarial RobustnessFraud Detection	CodeCode Available
An engine to simulate insurance fraud network data	Aug 21, 2023	Fraud Detection	CodeCode Available
Enhancing Fairness in Unsupervised Graph Anomaly Detection through Disentanglement	Jun 3, 2024	Anomaly DetectionDecision Making	CodeCode Available
GraphFC: Customs Fraud Detection with Label Scarcity	May 19, 2023	Fraud DetectionGraph Neural Network	CodeCode Available
Crowdsourcing Fraud Detection over Heterogeneous Temporal MMMA Graph	Aug 5, 2023	Anomaly DetectionFraud Detection	CodeCode Available
Financial Fraud Detection using Jump-Attentive Graph Neural Networks	Nov 7, 2024	Fraud Detection	CodeCode Available
Deep-Net: Deep Neural Network for Cyber Security Use Cases	Dec 9, 2018	Fraud DetectionGeneral Classification	CodeCode Available
Federated Spectral Graph Transformers Meet Neural Ordinary Differential Equations for Non-IID Graphs	Apr 16, 2025	Federated LearningFraud Detection	CodeCode Available
ARMS: Automated rules management system for fraud detection	Feb 14, 2020	Fraud DetectionHeuristic Search	CodeCode Available
SeqNAS: Neural Architecture Search for Event Sequence Classification	Jan 6, 2024	Bayesian OptimizationClassification	CodeCode Available
Deep Anomaly Detection with Deviation Networks	Nov 19, 2019	Anomaly DetectionCyber Attack Detection	CodeCode Available
Federated Graph Learning with Structure Proxy Alignment	Aug 18, 2024	Federated LearningFraud Detection	CodeCode Available
Graph similarity learning for change-point detection in dynamic networks	Mar 29, 2022	Change Point DetectionFraud Detection	CodeCode Available
Multiple perspectives HMM-based feature engineering for credit card fraud detection	May 15, 2019	Feature EngineeringFraud Detection	CodeCode Available
AUC-Oriented Domain Adaptation: From Theory to Algorithm	Aug 10, 2023	Disease PredictionDomain Adaptation	CodeCode Available
Higher-Order Label Homogeneity and Spreading in Graphs	Feb 18, 2020	Fraud DetectionRecommendation Systems	CodeCode Available
Adversarial Explanations for Understanding Image Classification Decisions and Improved Neural Network Robustness	Jun 7, 2019	Adversarial DefenseFraud Detection	CodeCode Available
High Performance Computing Applied to Logistic Regression: A CPU and GPU Implementation Comparison	Aug 19, 2023	Binary ClassificationCPU	CodeCode Available
VOS: a Method for Variational Oversampling of Imbalanced Data	Sep 7, 2018	Fraud DetectionGeneral Classification	CodeCode Available
Enhancing Ethereum Fraud Detection via Generative and Contrastive Self-supervision	Aug 1, 2024	Fraud Detection	CodeCode Available
How effective are Graph Neural Networks in Fraud Detection for Network Data?	May 30, 2021	Fraud Detection	CodeCode Available
Network analytics for insurance fraud detection: a critical case study	May 14, 2024	Fraud Detection	CodeCode Available

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All datasets BAF – Base Yelp-Fraud Amazon-Fraud Elliptic Dataset Healthcare Provider Fraud Detection Analysis Kaggle-Credit Card Fraud Dataset BAF – Variant I BAF – Variant II BAF – Variant III BAF – Variant IV BAF – Variant V FDCompCN

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	LightGBM	Recall @ 5% FPR	54.3	—	Unverified
2	CatBoost	Recall @ 5% FPR	52.4	—	Unverified
3	LightGBM	Recall @ 5% FPR	51.76	—	Unverified
4	1D-CSNN	Recall @ 5% FPR	50.35	—	Unverified
5	MLP–NN	Recall @ 5% FPR	49.6	—	Unverified
6	1D-CSNN	Recall @ 5% FPR	42.79	—	Unverified
7	LightGBM	Recall @ 1% FPR	25.2	—	Unverified
8	FIGS	Recall @ 1% FPR	21	—	Unverified
9	CART+RIFF	Recall @ 1% FPR	18.4	—	Unverified
10	CART	Recall @ 1% FPR	16	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LEX-GNN	AUC-ROC	96.4	—	Unverified
2	JA-GNN	AUC-ROC	95.11	—	Unverified
3	GTAN	AUC-ROC	94.98	—	Unverified
4	BOLT-GRAPH	AUC-ROC	93.18	—	Unverified
5	SplitGNN	AUC-ROC	92.03	—	Unverified
6	GAT+JK	AUC-ROC	90.04	—	Unverified
7	RLC-GNN	AUC-ROC	85.44	—	Unverified
8	RioGNN	AUC-ROC	83.54	—	Unverified
9	PC-GNN	AUC-ROC	79.87	—	Unverified
10	CARE-GNN	AUC-ROC	75.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LEX-GNN	AUC-ROC	97.91	—	Unverified
2	GTAN	AUC-ROC	97.5	—	Unverified
3	RLC-GNN	AUC-ROC	97.48	—	Unverified
4	RioGNN	AUC-ROC	96.19	—	Unverified
5	PC-GNN	AUC-ROC	95.86	—	Unverified
6	CARE-GNN	AUC-ROC	89.73	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	GCN	AUC	0.83	—	Unverified
2	GraphSAGE	AUC	0.83	—	Unverified
3	GAT	AUC	0.81	—	Unverified
4	GIN	AUC	0.81	—	Unverified
5	Node2vec	AUC	0.53	—	Unverified
6	Deepwalk	AUC	0.45	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BiRank	AUC	0.79	—	Unverified
2	GraphSAGE	AUC	0.67	—	Unverified
3	metapath2vec	AUC	0.51	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	XBNET	Accuracy	71.33	—	Unverified
2	DevNet	AUC	0.98	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	1D-CSNN	Recall @ 5% FPR	40.71	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	1D-CSNN	Recall @ 5% FPR	47.08	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	1D-CSNN	Recall @ 5% FPR	41.83	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	1D-CSNN	Recall @ 5% FPR	35.54	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	1D-CSNN	Recall @ 5% FPR	34.96	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SplitGNN	AUC-ROC	68.98	—	Unverified