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 451–475 of 547 papers

Title	Date	Tasks	Status
Deep Feature Fusion for Mitosis Counting	Feb 1, 2020	Fraud Detectionobject-detection	—Unverified
RePAD: Real-time Proactive Anomaly Detection for Time Series	Jan 24, 2020	Anomaly DetectionFraud Detection	—Unverified
Robust Graph Representation Learning via Neural Sparsification	Jan 1, 2020	Fraud DetectionGraph Representation Learning	CodeCode Available
EnsemFDet: An Ensemble Approach to Fraud Detection based on Bipartite Graph	Dec 23, 2019	Fraud Detection	—Unverified
NFAD: Fixing anomaly detection using normalizing flows	Dec 19, 2019	Anomaly DetectionBayesian Inference	CodeCode Available
Fraud detection in telephone conversations for financial services using linguistic features	Dec 10, 2019	Fraud Detection	—Unverified
A Comprehensive Survey on Machine Learning Techniques and User Authentication Approaches for Credit Card Fraud Detection	Dec 2, 2019	BIG-bench Machine LearningFraud Detection	—Unverified
Deep Anomaly Detection with Deviation Networks	Nov 19, 2019	Anomaly DetectionCyber Attack Detection	CodeCode Available
Quick survey of graph-based fraud detection methods	Oct 24, 2019	Anomaly DetectionFraud Detection	—Unverified
GenSample: A Genetic Algorithm for Oversampling in Imbalanced Datasets	Oct 23, 2019	Fraud DetectionMedical Diagnosis	—Unverified
WOTBoost: Weighted Oversampling Technique in Boosting for imbalanced learning	Oct 17, 2019	Fraud DetectionGeneral Classification	—Unverified
Kernel density estimation based sampling for imbalanced class distribution	Oct 17, 2019	Density EstimationFraud Detection	—Unverified
Detecting organized eCommerce fraud using scalable categorical clustering	Oct 10, 2019	ClusteringFraud Detection	CodeCode Available
The Area of the Convex Hull of Sampled Curves: a Robust Functional Statistical Depth Measure	Oct 9, 2019	Anomaly DetectionFraud Detection	CodeCode Available
Sequence embeddings help to identify fraudulent cases in healthcare insurance	Oct 7, 2019	Fraud DetectionManagement	—Unverified
Change Detection in Noisy Dynamic Networks: A Spectral Embedding Approach	Oct 5, 2019	Change DetectionFraud Detection	—Unverified
Detection of fraudulent users in P2P financial market	Sep 24, 2019	BIG-bench Machine LearningFraud Detection	—Unverified
A review on ranking problems in statistical learning	Sep 6, 2019	Document RankingFraud Detection	—Unverified
FraudJudger: Real-World Data Oriented Fraud Detection on Digital Payment Platforms	Sep 5, 2019	Fraud Detection	—Unverified
Minimizing the Societal Cost of Credit Card Fraud with Limited and Imbalanced Data	Sep 3, 2019	BIG-bench Machine LearningBlocking	—Unverified
Towards automated feature engineering for credit card fraud detection using multi-perspective HMMs	Sep 3, 2019	Automated Feature EngineeringFeature Engineering	CodeCode Available
An Adjusted Nearest Neighbor Algorithm Maximizing the F-Measure from Imbalanced Data	Sep 2, 2019	Fraud Detection	—Unverified
Credit Card Fraud Detection Using Autoencoder Neural Network	Aug 30, 2019	DenoisingFraud Detection	CodeCode Available
Solve fraud detection problem by using graph based learning methods	Aug 29, 2019	Fraud Detection	—Unverified
Are You for Real? Detecting Identity Fraud via Dialogue Interactions	Aug 19, 2019	Dialogue ManagementFraud Detection	CodeCode Available

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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