Simplifying the Data Tier for Real-Time Fraud Detection

Fraud is a billion-dollar business and increases every year. In 2019, 62% of breached data came from the financial services industry alone. With financial institutions increasing their investments into digital channels, their exposure to new threats will only intensify. While risk management leaders are focused on mitigating this growing threat, they are challenged by the inability of traditional data platforms to handle the speed, scale, and complexity of new online transactions.

In this session, we will discuss how Redis Enterprise is used by risk management professionals to support real-time fraud detection across digital identities, statistical analysis, AI transaction risk-scoring, anomaly detection, and more. Learn how you can leverage a multi-model in-memory database to expedite frictionless online transactions and reduce false positives without overcomplicating your enterprise architecture or external vendor solutions.

Key points covered:

  • Increasing investment into digital channels exposes financial institutions to new threats 
  • Traditional data platforms were not built to handle the speed, scale, and complexity of online transactions
  • Learn how Redis Enterprise is used to support real-time fraud detection across digital identities, statistical analysis, AI transaction risk-scoring, anomaly detection, and more
When:Oct 21, 2020 | 9:00 AM PDT
Duration:15 min
Featured Speaker:Allen Terleto, Field CTO, Redis Labs
Audience:Developers

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ABOUT THE SPEAKER

Allen Terleto, Field CTO, Redis Labs

Allen is Field CTO at Redis Labs where he helps organizations reimagine how quickly they can process, analyze, predict, and take data-driven actions. As the home of Redis, the most popular open source database, Redis Labs provides a competitive edge to global businesses with Redis Enterprise by delivering superior performance, multi-model capability, unmatched reliability, and the best total cost of ownership across on-premise, hybrid, and multi-cloud environments.

Allen has broad technical and business experience with a specialization in distributed, low-latency, and high-throughput mission critical systems. He is a trusted advisor to Redis Labs customers which include leading global banking institutions, fintechs, neobanks, and financial service providers.

He received his Advanced Graduate Certificate in Enterprise Risk Management from New York University (NYU) along with his Bachelor’s Degree in Computer Science and holds both an MBA and MSIS from Stevens Institute of Technology.