Data science Use case
detection-fraud-01

Fraud detection

Digitalisation may well lead financial services to innovative solutions, but such highly sensitive services must be secured to prevent criminal intrusions. Machine learning shines in that field, analysing big chunks of transactions and detecting potentially fraudulent behaviour.

The main challenge in fraud detection use cases is to combine high-velocity data from the payments, with data coming from operational systems such as user profiles, history of payments…

By using Digazu, you will significantly reduce the time to implement all the necessary steps needed for this task: collecting data, building data pipelines, developing your fraud detection model and deploying it as a scalable real-time microservice in an all-in-one secured and controlled environment.