SOTAVerified

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 AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 251–300 of 547 papers

TitleStatusHype
Crowdsourcing Fraud Detection over Heterogeneous Temporal MMMA GraphCode0
FPR Estimation for Fraud Detection in the Presence of Class-Conditional Label NoiseCode0
Graph Anomaly Detection at Group Level: A Topology Pattern Enhanced Unsupervised Approach—0
VertexSerum: Poisoning Graph Neural Networks for Link Inference—0
Using Kernel SHAP XAI Method to optimize the Network Anomaly Detection Model—0
Adversarial training for tabular data with attack propagation—0
Towards Reliable Rare Category Analysis on Graphs via Individual CalibrationCode0
Transaction Fraud Detection via Spatial-Temporal-Aware Graph Transformer—0
Transaction Fraud Detection via an Adaptive Graph Neural Network—0
LogitMat : Zeroshot Learning Algorithm for Recommender Systems without Transfer Learning or Pretrained Models—0
Adversarial Learning in Real-World Fraud Detection: Challenges and Perspectives—0
Synthetic Demographic Data Generation for Card Fraud Detection Using GANsCode0
Transferable Adversarial Robustness for Categorical Data via Universal Robust EmbeddingsCode0
Query Complexity of Active Learning for Function Family With Nearly Orthogonal Basis—0
Addressing Budget Allocation and Revenue Allocation in Data Market Environments Using an Adaptive Sampling AlgorithmCode0
Exploring Global and Local Information for Anomaly Detection with Normal Samples—0
Credit Card Fraud Detection Using Asexual Reproduction Optimization—0
GraphFC: Customs Fraud Detection with Label ScarcityCode0
Self-Reinforcement Attention Mechanism For Tabular Learning—0
Efficient Vertical Federated Learning with Secure Aggregation—0
Leveraging Machine Learning for Multichain DeFi Fraud Detection—0
Incremental Outlier Detection Modelling Using Streaming Analytics in Finance & Health Care—0
Automatic Procurement Fraud Detection with Machine Learning—0
BadVFL: Backdoor Attacks in Vertical Federated Learning—0
Bent & Broken Bicycles: Leveraging synthetic data for damaged object re-identification—0
BOLT: An Automated Deep Learning Framework for Training and Deploying Large-Scale Search and Recommendation Models on Commodity CPU HardwareCode0
Evaluating XGBoost for Balanced and Imbalanced Data: Application to Fraud Detection—0
Credit Card Fraud Detection Using Enhanced Random Forest Classifier for Imbalanced Data—0
ATM Fraud Detection using Streaming Data Analytics—0
Neural-based classification rule learning for sequential data—0
Deep Anomaly Detection under Labeling Budget ConstraintsCode0
A Case Study on Designing Evaluations of ML Explanations with Simulated User Studies—0
Efficient Fraud Detection Using Deep Boosting Decision TreesCode0
Fairness-aware Multi-view ClusteringCode0
A Comparison of Decision Forest Inference Platforms from A Database Perspective—0
Experimenting with an Evaluation Framework for Imbalanced Data Learning (EFIDL)—0
A Survey on Actionable Knowledge—0
Temporal Motifs for Financial Networks: A Study on Mercari, JPMC, and Venmo Platforms—0
AutoFraudNet: A Multimodal Network to Detect Fraud in the Auto Insurance Industry—0
Chaotic Variational Auto Encoder based One Class Classifier for Insurance Fraud Detection—0
Privacy-Preserving Collaborative Learning through Feature Extraction—0
Fraud Analytics: A Decade of Research -- Organizing Challenges and Solutions in the Field—0
A Time Series Approach to Explainability for Neural Nets with Applications to Risk-Management and Fraud Detection—0
A Privacy-Preserving Outsourced Data Model in Cloud Environment—0
Motif-aware temporal GCN for fraud detection in signed cryptocurrency trust networks—0
Explainable Artificial Intelligence and Causal Inference based ATM Fraud Detection—0
PU GNN: Chargeback Fraud Detection in P2E MMORPGs via Graph Attention Networks with Imbalanced PU Labels—0
Privacy-Preserving Credit Card Fraud Detection using Homomorphic EncryptionCode0
Unsupervised Machine Learning for Explainable Health Care Fraud Detection—0
Fraudulent User Detection Via Behavior Information Aggregation Network (BIAN) On Large-Scale Financial Social Network—0
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All datasetsBAF – BaseYelp-FraudAmazon-FraudElliptic DatasetHealthcare Provider Fraud Detection AnalysisKaggle-Credit Card Fraud DatasetBAF – Variant IBAF – Variant IIBAF – Variant IIIBAF – Variant IVBAF – Variant VFDCompCN

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1LightGBMRecall @ 5% FPR54.3—Unverified
2CatBoostRecall @ 5% FPR52.4—Unverified
3LightGBMRecall @ 5% FPR51.76—Unverified
41D-CSNNRecall @ 5% FPR50.35—Unverified
5MLP–NNRecall @ 5% FPR49.6—Unverified
61D-CSNNRecall @ 5% FPR42.79—Unverified
7LightGBMRecall @ 1% FPR25.2—Unverified
8FIGSRecall @ 1% FPR21—Unverified
9CART+RIFFRecall @ 1% FPR18.4—Unverified
10CARTRecall @ 1% FPR16—Unverified
#ModelMetricClaimedVerifiedStatus
1LEX-GNNAUC-ROC96.4—Unverified
2JA-GNNAUC-ROC95.11—Unverified
3GTANAUC-ROC94.98—Unverified
4BOLT-GRAPHAUC-ROC93.18—Unverified
5SplitGNNAUC-ROC92.03—Unverified
6GAT+JKAUC-ROC90.04—Unverified
7RLC-GNNAUC-ROC85.44—Unverified
8RioGNNAUC-ROC83.54—Unverified
9PC-GNNAUC-ROC79.87—Unverified
10CARE-GNNAUC-ROC75.7—Unverified
#ModelMetricClaimedVerifiedStatus
1LEX-GNNAUC-ROC97.91—Unverified
2GTANAUC-ROC97.5—Unverified
3RLC-GNNAUC-ROC97.48—Unverified
4RioGNNAUC-ROC96.19—Unverified
5PC-GNNAUC-ROC95.86—Unverified
6CARE-GNNAUC-ROC89.73—Unverified
#ModelMetricClaimedVerifiedStatus
1GCNAUC0.83—Unverified
2GraphSAGEAUC0.83—Unverified
3GATAUC0.81—Unverified
4GINAUC0.81—Unverified
5Node2vecAUC0.53—Unverified
6DeepwalkAUC0.45—Unverified
#ModelMetricClaimedVerifiedStatus
1BiRankAUC0.79—Unverified
2GraphSAGEAUC0.67—Unverified
3metapath2vecAUC0.51—Unverified
#ModelMetricClaimedVerifiedStatus
1XBNETAccuracy71.33—Unverified
2DevNetAUC0.98—Unverified
#ModelMetricClaimedVerifiedStatus
11D-CSNNRecall @ 5% FPR40.71—Unverified
#ModelMetricClaimedVerifiedStatus
11D-CSNNRecall @ 5% FPR47.08—Unverified
#ModelMetricClaimedVerifiedStatus
11D-CSNNRecall @ 5% FPR41.83—Unverified
#ModelMetricClaimedVerifiedStatus
11D-CSNNRecall @ 5% FPR35.54—Unverified
#ModelMetricClaimedVerifiedStatus
11D-CSNNRecall @ 5% FPR34.96—Unverified
#ModelMetricClaimedVerifiedStatus
1SplitGNNAUC-ROC68.98—Unverified