Faster fraud detection with better UX.
The shift to digital services like mobile banking, eCommerce, and insurance has caused a surge in online fraud of all types. According to Juniper Research, cumulative losses to online payment fraud globally between now and 2027 will exceed $343 billion. The increased complexity, volume, and speed of today’s online transactions mean that organizations need to use more advanced fraud detection methods to protect customers.
Join this demo to learn:
- How utilizing a real-time multi-model data platform can enable digital identity validation and AI/ML models to predict fraudulent transactions with fast responses to improve customer satisfaction and decrease churn.
- Storing and retrieving digital identity data to help companies process dynamic and complex identity elements across multiple data sources and types to validate a user’s identity, actions, or access.
- Transaction risk scoring to enable faster dynamic ML features for real-time machine learning model inferencing
Event Speaker
Henry Tam
Principal Solutions Marketing Manager
Redis
