Case Study: Azul Linhas Aereas reduces fraud false positives with Mangopay's Fraud Prevention solution

Azul Linhas Aereas detects 89% of fraudulent transactions with MANGOPAY

Azul Linhas Aereas, a Brazilian airline, sought to enhance its anti-fraud capabilities. Their goal was to reduce their false positives rate and the number of time-consuming manual reviews to cut operational costs. They also needed an advanced solution to identify new types of fraud while ensuring a frictionless customer experience.

Mangopay implemented its advanced fraud prevention solution, which utilizes machine learning, behavioral biometrics, and digital fingerprinting. This allowed Azul to precisely distinguish between good customers and fraud actors. The solution detected 89% of fraudulent transactions during a specific attack, compared to just 16% with their previous system. As a result, Azul prevented revenue loss through reduced chargebacks and lowered operational costs due to fewer manual reviews.

Azul Linhas Aereas