People’s financial activities with banks are increasingly migrating to digital platforms. Banks, which are large institutions that move money are transforming into Software Engineering Companies. At the core of modern banks is a large network of systems and platforms that capture, collect, process and analyze the digital data. Collecting and analyzing customers’ activities in real-time is critical for modern financial institutions to succeed.
In this talk we present a business use case where Capital One needs to process customer activities real-time and react to events appropriately as needed. We then present our experience in building a real-time analytics application that serves the business using a set of open source software frameworks with Apache Flink at its core for real-time stream processing engine. We then show a demo of running system serving our use case. Apache Flink with its real-time event processing capability that supports true event-time and its sophisticated windowing semantics is an ideal candidate for our application. We conclude the talk by putting the architecture of this application in the context of generic stream analytics framework and how many other Capital One’s use cases such as fraud detection, can be served with this analytics platform.
Srinivas’ talk is now available on the Chariot Solutions site.
Tags: big data, flink, frameworks, stream processing
Location: Salon A
April 12th, 2016
1:30 PM - 2:30 PM