Abstract
This research paper analyzes telecom fraud patterns, detection methodologies, and prevention strategies, providing insights into protecting against various types of telecom fraud and revenue loss. The study examines machine learning approaches for fraud detection.
Document
Fraud Detection
Pattern Recognition
Prevention Strategies
Revenue Protection
Risk Assessment
Machine Learning
Anomaly Detection
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Document Information
- Type: Research Paper
- Date: 2024-02-10
- Source: ACM Digital Library
- Category: Fraud Detection & Prevention
- File: Bypass_Fraud.pdf
Dr. Amanda Davis
ACM Digital Library
Fraud Detection ExpertDr. Rachel Green
Stanford University
Machine Learning SpecialistProf. Thomas Lee
MIT Sloan
Risk Management Expert