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 126–150 of 547 papers

Title	Date	Tasks	Status	Score
Fairness-aware Multi-view Clustering	Feb 11, 2023	ClusteringContrastive Learning	CodeCode Available	5
Federated Spectral Graph Transformers Meet Neural Ordinary Differential Equations for Non-IID Graphs	Apr 16, 2025	Federated LearningFraud Detection	CodeCode Available	5
Explaining Arguments' Strength: Unveiling the Role of Attacks and Supports (Technical Report)	Apr 22, 2024	Fraud Detection	CodeCode Available	5
Cyber Security Data Science: Machine Learning Methods and their Performance on Imbalanced Datasets	May 7, 2025	Anomaly DetectionBinary Classification	CodeCode Available	5
Evaluating the Efficacy of Instance Incremental vs. Batch Learning in Delayed Label Environments: An Empirical Study on Tabular Data Streaming for Fraud Detection	Sep 16, 2024	Computational EfficiencyFraud Detection	CodeCode Available	5
Exploring Neural Joint Activity in Spiking Neural Networks for Fraud Detection	Nov 17, 2024	Bayesian OptimizationFairness	CodeCode Available	5
RAGFormer: Learning Semantic Attributes and Topological Structure for Fraud Detection	Feb 27, 2024	Fraud DetectionRelation	CodeCode Available	5
A Semi-supervised Graph Attentive Network for Financial Fraud Detection	Feb 28, 2020	Fraud DetectionGraph Neural Network	CodeCode Available	5
Efficient Fraud Detection Using Deep Boosting Decision Trees	Feb 12, 2023	Fraud DetectionRepresentation Learning	CodeCode Available	5
Enhancing Ethereum Fraud Detection via Generative and Contrastive Self-supervision	Aug 1, 2024	Fraud Detection	CodeCode Available	5
Dynamic Feature Fusion: Combining Global Graph Structures and Local Semantics for Blockchain Fraud Detection	Jan 3, 2025	Fraud Detectiongraph construction	CodeCode Available	5
ARMS: Automated rules management system for fraud detection	Feb 14, 2020	Fraud DetectionHeuristic Search	CodeCode Available	5
A Framework for Large Scale Synthetic Graph Dataset Generation	Oct 4, 2022	BenchmarkingDataset Generation	CodeCode Available	5
Are You for Real? Detecting Identity Fraud via Dialogue Interactions	Aug 19, 2019	Dialogue ManagementFraud Detection	CodeCode Available	5
Crowdsourcing Fraud Detection over Heterogeneous Temporal MMMA Graph	Aug 5, 2023	Anomaly DetectionFraud Detection	CodeCode Available	5
Dual-channel Heterophilic Message Passing for Graph Fraud Detection	Apr 19, 2025	Fraud DetectionInductive Bias	CodeCode Available	5
Enhancing Fairness in Unsupervised Graph Anomaly Detection through Disentanglement	Jun 3, 2024	Anomaly DetectionDecision Making	CodeCode Available	5
Credit Card Fraud Detection Using Autoencoder Neural Network	Aug 30, 2019	DenoisingFraud Detection	CodeCode Available	5
Distributed Monitoring for Data Distribution Shifts in Edge-ML Fraud Detection	Jan 10, 2024	Fraud Detection	CodeCode Available	5
Data Distribution Valuation	Oct 6, 2024	Data ValuationFraud Detection	CodeCode Available	5
Explainable Fraud Detection with Deep Symbolic Classification	Dec 1, 2023	ClassificationFraud Detection	CodeCode Available	5
Diversity-Aware Weighted Majority Vote Classifier for Imbalanced Data	Apr 16, 2020	Binary ClassificationClassification	CodeCode Available	5
DistDGL: Distributed Graph Neural Network Training for Billion-Scale Graphs	Oct 11, 2020	Fraud DetectionGraph Neural Network	CodeCode Available	5
Deep-Net: Deep Neural Network for Cyber Security Use Cases	Dec 9, 2018	Fraud DetectionGeneral Classification	CodeCode Available	5
Detecting organized eCommerce fraud using scalable categorical clustering	Oct 10, 2019	ClusteringFraud Detection	CodeCode Available	5

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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