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 101–150 of 547 papers

TitleStatusHype
Corporate Fraud Detection in Rich-yet-Noisy Financial GraphCode0
Structural Alignment Improves Graph Test-Time Adaptation—0
Using Machine Learning to Detect Fraudulent SMSs in Chichewa—0
ML-Driven Approaches to Combat Medicare Fraud: Advances in Class Imbalance Solutions, Feature Engineering, Adaptive Learning, and Business Impact—0
Pub-Guard-LLM: Detecting Fraudulent Biomedical Articles with Reliable ExplanationsCode0
Financial fraud detection system based on improved random forest and gradient boosting machine (GBM)—0
Agentic AI Systems Applied to tasks in Financial Services: Modeling and model risk management crews—0
FRAUD-RLA: A new reinforcement learning adversarial attack against credit card fraud detection—0
Using Causality for Enhanced Prediction of Web Traffic Time Series—0
Explainability in Practice: A Survey of Explainable NLP Across Various Domains—0
Year-over-Year Developments in Financial Fraud Detection via Deep Learning: A Systematic Literature Review—0
Free Agent in Agent-Based Mixture-of-Experts Generative AI Framework—0
Advanced Real-Time Fraud Detection Using RAG-Based LLMs—0
Optimizing Blockchain Analysis: Tackling Temporality and Scalability with an Incremental Approach with Metropolis-Hastings Random Walks—0
SCFCRC: Simultaneously Counteract Feature Camouflage and Relation Camouflage for Fraud Detection—0
AI-based Identity Fraud Detection: A Systematic Review—0
Attention is All You Need Until You Need Retention—0
Detection of AI Deepfake and Fraud in Online Payments Using GAN-Based Models—0
Dynamic Feature Fusion: Combining Global Graph Structures and Local Semantics for Blockchain Fraud DetectionCode0
An Efficient Outlier Detection Algorithm for Data Streaming—0
Comparative Performance Analysis of Quantum Machine Learning Architectures for Credit Card Fraud Detection—0
Scam Detection for Ethereum Smart Contracts: Leveraging Graph Representation Learning for Secure Blockchain—0
PyOD 2: A Python Library for Outlier Detection with LLM-powered Model Selection—0
Backdoor attacks on DNN and GBDT -- A Case Study from the insurance domain—0
Impact of Sampling Techniques and Data Leakage on XGBoost Performance in Credit Card Fraud Detection—0
Blockchain Data Analysis in the Era of Large-Language Models—0
Multi-task CNN Behavioral Embedding Model For Transaction Fraud Detection—0
UMGAD: Unsupervised Multiplex Graph Anomaly Detection—0
Exploring Neural Joint Activity in Spiking Neural Networks for Fraud DetectionCode0
Partitioning Message Passing for Graph Fraud Detection—0
Improving Fraud Detection with 1D-Convolutional Spiking Neural Networks Through Bayesian OptimizationCode0
Differential Privacy Under Class Imbalance: Methods and Empirical Insights—0
GPT-Guided Monte Carlo Tree Search for Symbolic Regression in Financial Fraud Detection—0
Financial Fraud Detection using Jump-Attentive Graph Neural NetworksCode0
Enhancing Financial Fraud Detection with Human-in-the-Loop Feedback and Feedback Propagation—0
JEL: Applying End-to-End Neural Entity Linking in JPMorgan Chase—0
Graph Neural Networks for Financial Fraud Detection: A Review—0
Integrating Fuzzy Logic into Deep Symbolic Regression—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
Differentiable Inductive Logic Programming for Fraud Detection—0
A Systematic Review of Machine Learning in Sports Betting: Techniques, Challenges, and Future Directions—0
Proactive Fraud Defense: Machine Learning's Evolving Role in Protecting Against Online Fraud—0
Data Obfuscation through Latent Space Projection (LSP) for Privacy-Preserving AI Governance: Case Studies in Medical Diagnosis and Finance Fraud Detection—0
LEX-GNN: Label-Exploring Graph Neural Network for Accurate Fraud DetectionCode0
Redefining Finance: The Influence of Artificial Intelligence (AI) and Machine Learning (ML)—0
ASTM :Autonomous Smart Traffic Management System Using Artificial Intelligence CNN and LSTM—0
Enhanced Federated Anomaly Detection Through Autoencoders Using Summary Statistics-Based Thresholding—0
Heterogeneous Graph Auto-Encoder for CreditCard Fraud Detection—0
KnowGraph: Knowledge-Enabled Anomaly Detection via Logical Reasoning on Graph Data—0
Data Distribution ValuationCode0
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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