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 426–450 of 547 papers

Title	Date	Tasks	Status	Hype
I call BS: Fraud Detection in Crowdfunding Campaigns	Jun 30, 2020	BlockingFraud Detection	—Unverified	0
Graph Prototypical Networks for Few-shot Learning on Attributed Networks	Jun 23, 2020	ClassificationDrug Discovery	CodeCode Available	1
AutoOD: Automated Outlier Detection via Curiosity-guided Search and Self-imitation Learning	Jun 19, 2020	Fraud Detectionimage-classification	—Unverified	0
Robust Spammer Detection by Nash Reinforcement Learning	Jun 10, 2020	Fraud Detectionreinforcement-learning	CodeCode Available	1
DFraud3- Multi-Component Fraud Detection freeof Cold-start	Jun 10, 2020	Component ClassificationFraud Detection	—Unverified	0
Applying support vector data description for fraud detection	May 31, 2020	Fraud DetectionOne-Class Classification	—Unverified	0
Synthetic Observational Health Data with GANs: from slow adoption to a boom in medical research and ultimately digital twins?	May 27, 2020	BenchmarkingFraud Detection	—Unverified	0
Bayesian Stress Testing of Models in a Classification Hierarchy	May 25, 2020	BIG-bench Machine LearningClassification	CodeCode Available	0
Stealing Links from Graph Neural Networks	May 5, 2020	Fraud DetectionRecommendation Systems	CodeCode Available	1
Alleviating the Inconsistency Problem of Applying Graph Neural Network to Fraud Detection	May 1, 2020	Fraud DetectionGraph Neural Network	CodeCode Available	1
Diversity-Aware Weighted Majority Vote Classifier for Imbalanced Data	Apr 16, 2020	Binary ClassificationClassification	CodeCode Available	0
Spatio-Temporal Attention-Based Neural Network for Credit Card Fraud Detection	Apr 3, 2020	Fraud Detection	CodeCode Available	1
robROSE: A robust approach for dealing with imbalanced data in fraud detection	Mar 22, 2020	Anomaly DetectionFraud Detection	CodeCode Available	0
SUOD: Accelerating Large-Scale Unsupervised Heterogeneous Outlier Detection	Mar 11, 2020	Dimensionality ReductionFraud Detection	CodeCode Available	1
Industrial Scale Privacy Preserving Deep Neural Network	Mar 11, 2020	Fraud DetectionPrivacy Preserving	—Unverified	0
Link Prediction using Graph Neural Networks for Master Data Management	Mar 7, 2020	Fraud DetectionLink Prediction	—Unverified	0
InfDetect: a Large Scale Graph-based Fraud Detection System for E-Commerce Insurance	Mar 5, 2020	Fraud DetectionGraph Learning	—Unverified	0
An Information-Theoretic Approach to Personalized Explainable Machine Learning	Mar 1, 2020	BIG-bench Machine LearningDecision Making	—Unverified	0
A Semi-supervised Graph Attentive Network for Financial Fraud Detection	Feb 28, 2020	Fraud DetectionGraph Neural Network	CodeCode Available	0
Uncovering Insurance Fraud Conspiracy with Network Learning	Feb 27, 2020	Fraud DetectionGraph Learning	—Unverified	0
Adapted tree boosting for Transfer Learning	Feb 27, 2020	Fraud DetectionTransfer Learning	—Unverified	0
Higher-Order Label Homogeneity and Spreading in Graphs	Feb 18, 2020	Fraud DetectionRecommendation Systems	CodeCode Available	0
ARMS: Automated rules management system for fraud detection	Feb 14, 2020	Fraud DetectionHeuristic Search	CodeCode Available	0
Interleaved Sequence RNNs for Fraud Detection	Feb 14, 2020	Feature EngineeringFraud Detection	—Unverified	0
Privacy Preserving PCA for Multiparty Modeling	Feb 6, 2020	Fraud DetectionPrivacy Preserving	—Unverified	0

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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