Data in Motion Use Cases for Financial Services

Traditional systems were designed in an era that predates large-scale distributed systems. These systems often lack the ability to scale to meet the needs of the modern data-driven organisation. Adding to this is the accumulation of technologies and the explosion of data which can result in complex point-to-point integrations where data becomes siloed or separated across the enterprise.

The demand for fast results and decision making, have generated the need for real-time event streaming and processing of data adoption in financial institutions to be on the competitive edge. Apache Kafka® and the Confluent Platform are designed to solve the problems associated with traditional systems and provide a modern, distributed architecture and Real-time Data streaming capability. In addition these technologies open up a range of use cases for Financial Services organisations, many of which will be explored in this talk. .

Listened to Tom Green, Senior Solutions Engineer at Confluent, discuss the following use cases:

• How Data in Motion enables a 360 view of the customer
• How to provide a backbone for the distribution of trade data
• How Kafka and Confluent Platform enable you to meet regulatory requirements for trade information, payments, and liquidity
• How to overcome security concerns with SIEM
• How to integrate mainframe data with event streaming and the cloud
• How to reduce fraud with real-time fraud processing, fraud analytics and fraud notifications.
• How to Develop and enhance microservices.