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 351–375 of 547 papers

Title	Date	Tasks	Status
Global Confidence Degree Based Graph Neural Network for Financial Fraud Detection	Jul 24, 2024	Anomaly DetectionFraud Detection	—Unverified
Global Neighbor Sampling for Mixed CPU-GPU Training on Giant Graphs	Jun 11, 2021	CPUFraud Detection	—Unverified
GNNBleed: Inference Attacks to Unveil Private Edges in Graphs with Realistic Access to GNN Models	Nov 3, 2023	Fraud DetectionRecommendation Systems	—Unverified
GPT-Guided Monte Carlo Tree Search for Symbolic Regression in Financial Fraud Detection	Nov 7, 2024	Decision MakingFraud Detection	—Unverified
Graph Anomaly Detection at Group Level: A Topology Pattern Enhanced Unsupervised Approach	Aug 2, 2023	Anomaly DetectionContrastive Learning	—Unverified
Graph Anomaly Detection with Noisy Labels by Reinforcement Learning	Jul 8, 2024	Anomaly DetectionFraud Detection	—Unverified
Graph Computing for Financial Crime and Fraud Detection: Trends, Challenges and Outlook	Mar 2, 2021	Fraud Detection	—Unverified
GraphGuard: Contrastive Self-Supervised Learning for Credit-Card Fraud Detection in Multi-Relational Dynamic Graphs	Jul 17, 2024	Feature EngineeringFraud Detection	—Unverified
Graph Learning	Jul 8, 2025	Drug DiscoveryFairness	—Unverified
Graph Neural Networks for Financial Fraud Detection: A Review	Nov 1, 2024	Fraud Detection	—Unverified
Graph Neural Networks in Real-Time Fraud Detection with Lambda Architecture	Oct 9, 2021	Fraud Detectiongraph construction	—Unverified
Graph Neural Network Training with Data Tiering	Nov 10, 2021	CPUFraud Detection	—Unverified
Helen: Maliciously Secure Coopetitive Learning for Linear Models	Jul 16, 2019	Fraud Detection	—Unverified
Heterogeneous Graph Auto-Encoder for CreditCard Fraud Detection	Oct 10, 2024	Fraud Detection	—Unverified
Higher-order Structure Based Anomaly Detection on Attributed Networks	Jun 7, 2024	Anomaly DetectionAttribute	—Unverified
HitFraud: A Broad Learning Approach for Collective Fraud Detection in Heterogeneous Information Networks	Sep 13, 2017	Fraud Detection	—Unverified
How can I choose an explainer? An Application-grounded Evaluation of Post-hoc Explanations	Jan 21, 2021	Decision MakingExplainable Artificial Intelligence (XAI)	—Unverified
How Far Should We Look Back to Achieve Effective Real-Time Time-Series Anomaly Detection?	Feb 12, 2021	Anomaly DetectionFraud Detection	—Unverified
Hybrid Heuristic Algorithms for Adiabatic Quantum Machine Learning Models	Jul 26, 2024	Fraud DetectionQuantum Machine Learning	—Unverified
Hyperbolic Self-supervised Contrastive Learning Based Network Anomaly Detection	Sep 12, 2022	Anomaly DetectionContrastive Learning	—Unverified
I call BS: Fraud Detection in Crowdfunding Campaigns	Jun 30, 2020	BlockingFraud Detection	—Unverified
iLoRE: Dynamic Graph Representation with Instant Long-term Modeling and Re-occurrence Preservation	Sep 5, 2023	Fraud DetectionRepresentation Learning	—Unverified
Impact of Sampling Techniques and Data Leakage on XGBoost Performance in Credit Card Fraud Detection	Dec 10, 2024	Fraud Detection	—Unverified
Impact of the composition of feature extraction and class sampling in medicare fraud detection	Jun 3, 2022	Dimensionality ReductionFraud Detection	—Unverified
Improved Aggregating and Accelerating Training Methods for Spatial Graph Neural Networks on Fraud Detection	Feb 14, 2022	Fraud DetectionIncremental Learning	—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