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

Showing 451–500 of 547 papers

TitleStatusHype
PyOD 2: A Python Library for Outlier Detection with LLM-powered Model Selection—0
QFNN-FFD: Quantum Federated Neural Network for Financial Fraud Detection—0
Query Complexity of Active Learning for Function Family With Nearly Orthogonal Basis—0
Radial Autoencoders for Enhanced Anomaly Detection—0
Reconstruction Enhanced Multi-View Contrastive Learning for Anomaly Detection on Attributed Networks—0
Redefining Finance: The Influence of Artificial Intelligence (AI) and Machine Learning (ML)—0
Relational Graph Neural Networks for Fraud Detection in a Super-App environment—0
RePAD: Real-time Proactive Anomaly Detection for Time Series—0
ResBuilder: Automated Learning of Depth with Residual Structures—0
Rethinking Contrastive Learning in Graph Anomaly Detection: A Clean-View Perspective—0
Review of blockchain application with Graph Neural Networks, Graph Convolutional Networks and Convolutional Neural Networks—0
Review of Digital Asset Development with Graph Neural Network Unlearning—0
RIFF: Inducing Rules for Fraud Detection from Decision Trees—0
RLC-GNN: An Improved Deep Architecture for Spatial-Based Graph Neural Network with Application to Fraud Detection—0
RAGFormer: Learning Semantic Attributes and Topological Structure for Fraud DetectionCode0
Weight-of-evidence 2.0 with shrinkage and spline-binningCode0
GARG-AML against Smurfing: A Scalable and Interpretable Graph-Based Framework for Anti-Money LaunderingCode0
FPR Estimation for Fraud Detection in the Presence of Class-Conditional Label NoiseCode0
Synthetic Demographic Data Generation for Card Fraud Detection Using GANsCode0
Generating Multi-type Temporal Sequences to Mitigate Class-imbalanced ProblemCode0
A Semi-supervised Graph Attentive Network for Financial Fraud DetectionCode0
BOLT: An Automated Deep Learning Framework for Training and Deploying Large-Scale Search and Recommendation Models on Commodity CPU HardwareCode0
Detecting organized eCommerce fraud using scalable categorical clusteringCode0
Pub-Guard-LLM: Detecting Fraudulent Biomedical Articles with Reliable ExplanationsCode0
BigDL: A Distributed Deep Learning Framework for Big DataCode0
Bayesian Stress Testing of Models in a Classification HierarchyCode0
Modeling Heterogeneous Statistical Patterns in High-dimensional Data by Adversarial Distributions: An Unsupervised Generative FrameworkCode0
Financial Fraud Detection with Entropy ComputingCode0
Transferable Adversarial Robustness for Categorical Data via Universal Robust EmbeddingsCode0
An engine to simulate insurance fraud network dataCode0
Enhancing Fairness in Unsupervised Graph Anomaly Detection through DisentanglementCode0
GraphFC: Customs Fraud Detection with Label ScarcityCode0
Crowdsourcing Fraud Detection over Heterogeneous Temporal MMMA GraphCode0
Financial Fraud Detection using Jump-Attentive Graph Neural NetworksCode0
Deep-Net: Deep Neural Network for Cyber Security Use CasesCode0
Federated Spectral Graph Transformers Meet Neural Ordinary Differential Equations for Non-IID GraphsCode0
ARMS: Automated rules management system for fraud detectionCode0
SeqNAS: Neural Architecture Search for Event Sequence ClassificationCode0
Deep Anomaly Detection with Deviation NetworksCode0
Federated Graph Learning with Structure Proxy AlignmentCode0
Graph similarity learning for change-point detection in dynamic networksCode0
Multiple perspectives HMM-based feature engineering for credit card fraud detectionCode0
AUC-Oriented Domain Adaptation: From Theory to AlgorithmCode0
Higher-Order Label Homogeneity and Spreading in GraphsCode0
Adversarial Explanations for Understanding Image Classification Decisions and Improved Neural Network RobustnessCode0
High Performance Computing Applied to Logistic Regression: A CPU and GPU Implementation ComparisonCode0
VOS: a Method for Variational Oversampling of Imbalanced DataCode0
Enhancing Ethereum Fraud Detection via Generative and Contrastive Self-supervisionCode0
How effective are Graph Neural Networks in Fraud Detection for Network Data?Code0
Network analytics for insurance fraud detection: a critical case studyCode0
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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