Women in Data Science Puget Sound 2024

The retail sector is increasingly vulnerable to a variety of sophisticated fraud schemes that can lead to financial loss and erode consumer trust. This presentation will examine the escalating problem of retail fraud, identify the key challenges retailers face, and offer a comprehensive overview of an innovative solution leveraging the distributed event-streaming capabilities of Apache Kafka in conjunction with the real-time stream processing power of Apache Flink.

We will outline challenges in the retail industry, such as the need to process and analyze data in real-time to detect fraudulent patterns swiftly and the difficulty in scaling systems to handle peak transaction volumes.

The core of the session will provide an overview of the system's workflow, which employs Apache Kafka to efficiently handle high-volume data streams and Apache Flink for its low-latency processing capabilities. We will illustrate how these components interact to create a real-time fraud detection engine that can identify and act upon suspicious activities as they occur.

Next, we will delve into specific use cases, illustrating how the system addresses common fraud scenarios such as in-store return fraud, policy abuse and anomalous markdowns. Through these examples, attendees will gain insight into the system's versatility and its ability to mitigate various types of fraud across the retail domain.

The talk will also cover the results achieved by this system, including improved fraud detection rates, reduced false positives, and the ability to preempt fraud before it impacts the bottom line. We will highlight how this approach not only protects revenue but also enhances the customer experience by minimizing the intrusion of fraud checks on legitimate transactions.

Finally, we will explore other opportunities presented by this technology, including the incorporation of machine learning algorithms for enhanced predictive capabilities. These could utilize MLOps methodologies for model lifecycle management to ensure continuous adaptation and peak performance against emerging fraud tactics.

Attendees of this session will leave with a clear understanding of how the combined strengths of Apache Kafka and Apache Flink are shaping the future of real-time fraud prevention in the retail space, offering scalable, efficient, and adaptable solutions to this persistent industry challenge.