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 401–450 of 547 papers

TitleStatusHype
A comparative evaluation of novelty detection algorithms for discrete sequences—0
A Comparative Study on Unsupervised Anomaly Detection for Time Series: Experiments and Analysis—0
A Comparison of Decision Forest Inference Platforms from A Database Perspective—0
A Comparison Study of Credit Card Fraud Detection: Supervised versus Unsupervised—0
A Comprehensive Survey of Data Mining-based Fraud Detection Research—0
A Comprehensive Survey on Machine Learning Techniques and User Authentication Approaches for Credit Card Fraud Detection—0
Active learning for imbalanced data under cold start—0
A Customer Level Fraudulent Activity Detection Benchmark for Enhancing Machine Learning Model Research and Evaluation—0
Adapted tree boosting for Transfer Learning—0
Adaptive Stress Testing for Adversarial Learning in a Financial Environment—0
A Data Balancing and Ensemble Learning Approach for Credit Card Fraud Detection—0
Addressing Noise and Stochasticity in Fraud Detection for Service Networks—0
Advanced Financial Fraud Detection Using GNN-CL Model—0
Advanced fraud detection using machine learning models: enhancing financial transaction security—0
Advanced Real-Time Fraud Detection Using RAG-Based LLMs—0
Adversarial Attacks for Tabular Data: Application to Fraud Detection and Imbalanced Data—0
Adversarial Learning in Real-World Fraud Detection: Challenges and Perspectives—0
Adversarial training for tabular data with attack propagation—0
A Framework for Large Scale Synthetic Graph Dataset Generation—0
Agentic AI Systems Applied to tasks in Financial Services: Modeling and model risk management crews—0
AI-based Identity Fraud Detection: A Systematic Review—0
Aiding Humans in Financial Fraud Decision Making: Toward an XAI-Visualization Framework—0
AlertMix: A Big Data platform for multi-source streaming data—0
A Machine Learning Driven Website Platform and Browser Extension for Real-time Scoring and Fraud Detection for Website Legitimacy Verification and Consumer Protection—0
An Adjusted Nearest Neighbor Algorithm Maximizing the F-Measure from Imbalanced Data—0
Analysis of Communication Pattern with Scammers in Enron Corpus—0
An Attack Method for Medical Insurance Claim Fraud Detection based on Generative Adversarial Network—0
An Efficient Outlier Detection Algorithm for Data Streaming—0
A new perspective on classification: optimally allocating limited resources to uncertain tasks—0
An Information-Theoretic Approach to Personalized Explainable Machine Learning—0
Explainable AI for Fraud Detection: An Attention-Based Ensemble of CNNs, GNNs, and A Confidence-Driven Gating Mechanism—0
A Human-in-the-Loop Approach based on Explainability to Improve NTL Detection—0
Anomaly and Fraud Detection in Credit Card Transactions Using the ARIMA Model—0
Anomaly Detection in Power Generation Plants with Generative Adversarial Networks—0
Anomaly detection in wide area network mesh using two machine learning anomaly detection algorithms—0
Anomaly Detection using Capsule Networks for High-dimensional Datasets—0
A novel approach to increase scalability while training machine learning algorithms using Bfloat 16 in credit card fraud detection—0
Application of AI-based Models for Online Fraud Detection and Analysis—0
Application of Causal Inference to Analytical Customer Relationship Management in Banking and Insurance—0
Application of Deep Reinforcement Learning to Payment Fraud—0
Applications of Machine Learning in Fintech Credit Card Fraud Detection—0
Applying Quantum Autoencoders for Time Series Anomaly Detection—0
Applying support vector data description for fraud detection—0
Approaches to Fraud Detection on Credit Card Transactions Using Artificial Intelligence Methods—0
A Privacy-Preserving Outsourced Data Model in Cloud Environment—0
A proof that deep artificial neural networks overcome the curse of dimensionality in the numerical approximation of Kolmogorov partial differential equations with constant diffusion and nonlinear drift coefficients—0
A review on ranking problems in statistical learning—0
A Self-Attention Network for Hierarchical Data Structures with an Application to Claims Management—0
Supervised Graph Contrastive Learning for Few-shot Node Classification—0
ASTM :Autonomous Smart Traffic Management System Using Artificial Intelligence CNN and LSTM—0
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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