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 110 of 547 papers

TitleStatusHype
Graph Learning0
Temporal-Aware Graph Attention Network for Cryptocurrency Transaction Fraud Detection0
An Attack Method for Medical Insurance Claim Fraud Detection based on Generative Adversarial Network0
Secure Energy Transactions Using Blockchain Leveraging AI for Fraud Detection and Energy Market Stability0
FAA Framework: A Large Language Model-Based Approach for Credit Card Fraud Investigations0
Advanced fraud detection using machine learning models: enhancing financial transaction security0
EDINET-Bench: Evaluating LLMs on Complex Financial Tasks using Japanese Financial StatementsCode1
GARG-AML against Smurfing: A Scalable and Interpretable Graph-Based Framework for Anti-Money LaunderingCode0
Data Leakage and Deceptive Performance: A Critical Examination of Credit Card Fraud Detection Methodologies0
Rethinking Contrastive Learning in Graph Anomaly Detection: A Clean-View Perspective0
Show:102550
← PrevPage 1 of 55Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GCNAUC0.83Unverified
2GraphSAGEAUC0.83Unverified
3GATAUC0.81Unverified
4GINAUC0.81Unverified
5Node2vecAUC0.53Unverified
6DeepwalkAUC0.45Unverified