Capital One Delivers RiskInsights in Real Timewith Stream Processing

Capital One Delivers Risk Insights in Real Time with Stream Processing

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Capital One supports interactions with real-time streaming transactional data using Apache Kafka®. Kafka helps deliver information to internal operation teams and bank tellers to assist with assessing risk and protect customers in a myriad of ways.

Inside the bank, Kafka allows Capital One to build a real-time system that takes advantage of modern data and cloud technologies without exposing customers to unnecessary data breaches, or violating privacy regulations. These examples demonstrate how a streaming platform enables Capital One to act on their visions faster and in a more scalable way through the Kafka solution, helping establish Capital One as an innovator in the banking space.

Join us for this online talk on lessons learned, best practices and technical patterns of Capital One’s deployment of Apache Kafka. 

  • Find out how Kafka delivers on a 5-second service-level agreement (SLA) for inside branch tellers.
  • Learn how to combine and host data in-memory and prevent personally identifiable information (PII) violations of in-flight transactions.
  • Understand how Capital One manages Kafka Docker containers using Kubernetes.

Speakers

Ravi Dubey

Ravi Dubey, Senior Manager, Software Engineering, Capital One

Ravi is a senior manager working for Capital One in Virginia. Ravi has over 25 years of software development and management experience across a range of products in support of government and commercial industries. His most recent experience includes full stack development of web apps, cloud-based enterprise-facing support applications and a high-throughput, low-latency, distributed cloud-hosted data processing platform.

Jeff Sharpe

Jeff Sharpe, Senior Software Engineer, Capital One

Jeff is a senior software engineer working for Capital One in Virginia. He’s been an engineer for almost 18 years, with major projects spanning five different languages. Though he began his work on kernel drivers and web applications, he’s been repeatedly drawn into high volume, high throughput data processing projects.

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