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 171–180 of 547 papers

Title	Date	Tasks	Status
DetoxBench: Benchmarking Large Language Models for Multitask Fraud & Abuse Detection	Sep 9, 2024	Abuse DetectionAbusive Language	—Unverified
DFraud3- Multi-Component Fraud Detection freeof Cold-start	Jun 10, 2020	Component ClassificationFraud Detection	—Unverified
Differentiable Inductive Logic Programming for Fraud Detection	Oct 29, 2024	Fraud DetectionInductive logic programming	—Unverified
Differentially Private Secure Multi-Party Computation for Federated Learning in Financial Applications	Oct 12, 2020	Federated LearningFraud Detection	—Unverified
Differential Privacy Under Class Imbalance: Methods and Empirical Insights	Nov 8, 2024	Fraud DetectionPrivacy Preserving	—Unverified
Diffusion Boosted Trees	Jun 3, 2024	DenoisingFraud Detection	—Unverified
DistDGL: Distributed Graph Neural Network Training for Billion-Scale Graphs	Oct 11, 2020	Fraud DetectionGraph Neural Network	—Unverified
Distributed data analytics	Mar 26, 2022	Cloud ComputingFraud Detection	—Unverified
AutoOD: Automated Outlier Detection via Curiosity-guided Search and Self-imitation Learning	Jun 19, 2020	Fraud Detectionimage-classification	—Unverified
A Systematic Review of Machine Learning in Sports Betting: Techniques, Challenges, and Future Directions	Oct 28, 2024	Anomaly DetectionFairness	—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