Fraud Detection


Telecommunication industry being the one attracting almost the most significant number of users every day is a vast field for fraudulent activity. The most widespread cases of fraud in the telecom area are illegal access, authorization, theft or fake profiles, cloning, behavioral fraud, etc. Fraud has a direct influence on the relationship established between the company and the user.

By applying unsupervised machine learning algorithms to an immense amount of customer and operator data to spot the characteristics of normal traffic you can prevent fraud.

Benefits for the company

The value of fraud losses faced by the Telecom industry globally is around $40.1 billion which is around 1.88% of the total revenue.

Therefore, fraud detection systems, tools, and techniques can help companies save millions of dollars and increase network safety.



Type of expertise/ AI domain

Unsupervised Machine Learning, Anomalies Detection, Fuzzy Logic

Internal data required

Customer Usage Data, behvioral data, call data

One Response

  1. The algorithms define the anomalies and with the help of data visualization techniques present them as alerts to the analysts in real time. The efficiency of this technique is very high because it allows to provide an almost real-time response to the suspicious activity.

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