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 251–275 of 547 papers

Title	Date	Tasks	Status
Minimizing the Societal Cost of Credit Card Fraud with Limited and Imbalanced Data	Sep 3, 2019	BIG-bench Machine LearningBlocking	—Unverified
Minimum Enclosing Ball Synthetic Minority Oversampling Technique from a Geometric Perspective	Aug 7, 2024	Fraud DetectionMedical Diagnosis	—Unverified
MixBoost: Synthetic Oversampling with Boosted Mixup for Handling Extreme Imbalance	Sep 3, 2020	Data AugmentationFraud Detection	—Unverified
Mixed Quantum-Classical Method For Fraud Detection with Quantum Feature Selection	Aug 16, 2022	feature selectionFraud Detection	—Unverified
ML-Driven Approaches to Combat Medicare Fraud: Advances in Class Imbalance Solutions, Feature Engineering, Adaptive Learning, and Business Impact	Feb 21, 2025	DiagnosticDimensionality Reduction	—Unverified
Modeling the Field Value Variations and Field Interactions Simultaneously for Fraud Detection	Aug 8, 2020	Fraud DetectionManagement	—Unverified
Modeling Users' Behavior Sequences with Hierarchical Explainable Network for Cross-domain Fraud Detection	Jan 4, 2022	Fraud Detection	—Unverified
Motif-aware temporal GCN for fraud detection in signed cryptocurrency trust networks	Nov 22, 2022	Fraud Detection	—Unverified
Multi-future Merchant Transaction Prediction	Jul 10, 2020	DecoderFraud Detection	—Unverified
Multimodal and Contrastive Learning for Click Fraud Detection	May 8, 2021	Contrastive LearningFraud Detection	—Unverified
Multiple Attribute Fairness: Application to Fraud Detection	Jul 28, 2022	AttributeFairness	—Unverified
Multiple Inputs Neural Networks for Medicare fraud Detection	Mar 11, 2022	Anomaly DetectionFraud Detection	—Unverified
Deep Feature Fusion for Mitosis Counting	Feb 1, 2020	Fraud Detectionobject-detection	—Unverified
Multi-stream RNN for Merchant Transaction Prediction	Jul 25, 2020	Fraud DetectionPrediction	—Unverified
Multi-task CNN Behavioral Embedding Model For Transaction Fraud Detection	Nov 29, 2024	Fraud DetectionInductive Bias	—Unverified
Network In Graph Neural Network	Nov 23, 2021	Fraud DetectionGraph Neural Network	—Unverified
Neural-based classification rule learning for sequential data	Feb 22, 2023	Binary ClassificationClassification	—Unverified
New User Event Prediction Through the Lens of Causal Inference	Jul 8, 2024	Causal Inferencecounterfactual	—Unverified
Non-Parametric Stochastic Sequential Assignment With Random Arrival Times	Jun 9, 2021	Fraud Detection	—Unverified
Onion-Peeling Outlier Detection in 2-D data Sets	Mar 12, 2018	ClusteringFraud Detection	—Unverified
Online Anomaly Detection via Class-Imbalance Learning	Aug 27, 2015	Action DetectionActivity Detection	—Unverified
On some studies of Fraud Detection Pipeline and related issues from the scope of Ensemble Learning and Graph-based Learning	May 10, 2022	Ensemble LearningFraud Detection	—Unverified
On the Importance of Application-Grounded Experimental Design for Evaluating Explainable ML Methods	Jun 24, 2022	Experimental DesignFraud Detection	—Unverified
On the intrinsic robustness to noise of some leading classifiers and symmetric loss function -- an empirical evaluation	Oct 22, 2020	Fraud Detectionregression	—Unverified
On the Potential of Network-Based Features for Fraud Detection	Feb 14, 2024	Feature ImportanceFraud Detection	—Unverified

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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