The telecommunication industry is highly attractive for fraudulent activities as it is committed to a large number of customers. The number of customers increases every day and so is the interest of swindlers. Illegal or unauthorized access, cloning, behavioral fraud, fake profiles, theft of profiles, etc. are some of the common frauds in the telecom industry.

These frauds can severely impact customers and have a devastating influence on the relationship between the customer and the company. For that reason, fraud detection and prevention techniques have been highly important. Using unsupervised machine learning to identify the normal traffic on a channel can significantly impede fraud. These algorithms can process large datasets and provide alerts in real-time to initiate real-time responses to prevent fraud.