Case Study: Global Telecom Company reduces fraud risk with Fraud.net machine learning scoring

Global Telecom Company - Customer Case Study

Global Telecom Company, a telecommunications provider, faced growing fraud and loss risks across a complex business that spans retail equipment, wireless services, and consumer accounts. Fraud rings were driving account takeovers, porting fraud, and new application fraud, while customer payment defaults added further financial pressure. Fraud.net was brought in to help address these challenges.

Fraud.net implemented machine learning models tailored to telecom, using an adaptive scoring system that analyzes risk and delivers a single risk score in under 500 ms. The solution is designed to detect fraud more accurately and reduce losses, supporting lower operating costs and better decision-making.