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 101–125 of 547 papers

Title	Date	Tasks	Status	Score
High Performance Computing Applied to Logistic Regression: A CPU and GPU Implementation Comparison	Aug 19, 2023	Binary ClassificationCPU	CodeCode Available	5
BOLT: An Automated Deep Learning Framework for Training and Deploying Large-Scale Search and Recommendation Models on Commodity CPU Hardware	Mar 30, 2023	CPUFraud Detection	CodeCode Available	5
Modeling Heterogeneous Statistical Patterns in High-dimensional Data by Adversarial Distributions: An Unsupervised Generative Framework	Dec 15, 2020	Anomaly DetectionFraud Detection	CodeCode Available	5
robROSE: A robust approach for dealing with imbalanced data in fraud detection	Mar 22, 2020	Anomaly DetectionFraud Detection	CodeCode Available	5
FPR Estimation for Fraud Detection in the Presence of Class-Conditional Label Noise	Aug 4, 2023	Binary ClassificationFraud Detection	CodeCode Available	5
RAGFormer: Learning Semantic Attributes and Topological Structure for Fraud Detection	Feb 27, 2024	Fraud DetectionRelation	CodeCode Available	5
Financial Fraud Detection using Jump-Attentive Graph Neural Networks	Nov 7, 2024	Fraud Detection	CodeCode Available	5
An engine to simulate insurance fraud network data	Aug 21, 2023	Fraud Detection	CodeCode Available	5
LEX-GNN: Label-Exploring Graph Neural Network for Accurate Fraud Detection	Oct 21, 2024	Fraud DetectionGraph Neural Network	CodeCode Available	5
LIME: Low-Cost and Incremental Learning for Dynamic Heterogeneous Information Networks	Feb 11, 2021	Anomaly DetectionFraud Detection	CodeCode Available	5
Financial Fraud Detection with Entropy Computing	Mar 14, 2025	Fraud Detection	CodeCode Available	5
Federated Graph Learning with Structure Proxy Alignment	Aug 18, 2024	Federated LearningFraud Detection	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
Fairness-aware Multi-view Clustering	Feb 11, 2023	ClusteringContrastive Learning	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
Explainable Fraud Detection with Deep Symbolic Classification	Dec 1, 2023	ClassificationFraud Detection	CodeCode Available	5
Comparative Study on the Performance of Categorical Variable Encoders in Classification and Regression Tasks	Jan 18, 2024	Fraud Detection	CodeCode Available	5
AUC-Oriented Domain Adaptation: From Theory to Algorithm	Aug 10, 2023	Disease PredictionDomain Adaptation	CodeCode Available	5
Enhancing Fairness in Unsupervised Graph Anomaly Detection through Disentanglement	Jun 3, 2024	Anomaly DetectionDecision Making	CodeCode Available	5
Explaining Arguments' Strength: Unveiling the Role of Attacks and Supports (Technical Report)	Apr 22, 2024	Fraud Detection	CodeCode Available	5
Efficient Fraud Detection Using Deep Boosting Decision Trees	Feb 12, 2023	Fraud DetectionRepresentation Learning	CodeCode Available	5
Corporate Fraud Detection in Rich-yet-Noisy Financial Graph	Feb 26, 2025	Fraud DetectionKnowledge Graph Embeddings	CodeCode Available	5
Enhancing Ethereum Fraud Detection via Generative and Contrastive Self-supervision	Aug 1, 2024	Fraud Detection	CodeCode Available	5
Exploring Neural Joint Activity in Spiking Neural Networks for Fraud Detection	Nov 17, 2024	Bayesian OptimizationFairness	CodeCode Available	5
GARG-AML against Smurfing: A Scalable and Interpretable Graph-Based Framework for Anti-Money Laundering	Jun 4, 2025	Computational EfficiencyFraud 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