In the fiercely saturated telecom industry, revenue leakage poses a significant threat to profitability. Unidentified billing discrepancies can lead to lost revenue and impact customer trust. To effectively combat this challenge, telecom providers must implement robust strategies to signaling identify and rectify hidden revenue leakage points. This

SIM box fraud poses a significant danger to telecommunications providers worldwide, causing substantial financial losses and undermining network integrity. This insidious scheme involves the illegal interception and redirection of international calls through unauthorized devices known as SIM boxes. To combat this pervasive issue, it is crucial for

Telecommunication fraud/theft/deceit is a pervasive problem, costing service providers and consumers billions of dollars annually. Machine learning (ML) offers a powerful arsenal to combat this ever-evolving threat. By analyzing vast datasets of call records, network traffic, and user behavior patterns, ML algorithms can identify/detect/uncover ano