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Top 3 use cases for real time streams in financial services architectures

Market leaders in the finance industry have understood the power of data to reimagine their markets, customers, products, and business model. But this change doesn’t happen overnight. Traditional systems used for solving these problems were designed in an era that predates large-scale distributed systems and lack the ability to scale to meet the needs of the modern data-driven organization. Over time, the accumulation of technologies, accompanied by adding multiple lines of businesses, leads to complex point-to-point integrations where data becomes siloed or separated across the enterprise.


Streaming data for real-time finances with Confluent

The ideal architecture most envision is a clean, optimized system that allows businesses to capitalize on all that data. A streaming platform is designed to solve these problems with a modern, distributed architecture, eliminating the need for point-to-point connections. Instead it offers a single platform to publish and subscribe, store, and process streams of data in real-time, at any scale, in any environment, whether on-premise, or in the cloud.

Common use cases for this new development paradigm are for example customer 360 which allows to respond in real time to every customer experience, fraud detection by using a streaming platform as source for real-time data or mainframe offloading by re-directing data flows.

This whitepaper shows how real-time streaming can help companies achieve more growth, easier regulation management and minimized risk, making them smarter, faster, and more efficient.

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From traditional data integration to a streaming platform like Confluent

  1. Streaming data as an alternative to big data

  2. How streaming data impacts your strategic initiatives in the financial services industry

  3. Centralized, real-time, and scalable

  4. Real-time streams in real-world financial services