Financial institutions are increasing their investments in digital channels and automating complex workflows including risk management. This includes transaction risk scoring, fraud detection, automating loan approvals, and personalizing credit card offers, but all these processes are blocked when using traditional data platforms that can’t handle the speed, scale, and complexity of online transactional data.
In this session, you will learn how financial companies use Redis Enterprise, an in-memory data platform with sub-millisecond latency, linear scalability, and support for multiple data models, to unlock your trove of financial data to make better decisions, generate new business opportunities, and help mitigate risk.
Key Takeaways:
- Increasing digital processes and automating complex business decisions exposes legacy data systems
- Multi-model in-memory data platform expedites frictionless transactions, provides efficient risk scoring, and reduces false positives in detecting fraud, without adding complexity into your enterprise architecture
- Redis Enterprise submillisecond latency and scalability does matter in sustaining new digital volumes when moving to automated processes
