Fraud Detection System Design | System Design Interview | Real-Time Fraud Detection

In this video, we design a Fraud Detection System from scratch and walk through the architecture, components, data flow, scalability, and real-time decision-making involved in building a production-ready fraud detection platform. This is especially useful for System Design Interviews, Senior Software Engineer Interviews, Backend Engineer Interviews, and anyone preparing for Distributed Systems and Machine Learning System Design. What we cover: Fraud Detection System Architecture Real-time fraud detection Transaction processing Rules-based fraud detection Machine Learning fraud detection Kafka and event streaming High-throughput system design Low-latency fraud decisions Feature engineering and feature stores Fraud scoring Risk engine Database design Caching Scalability and fault tolerance Handling millions of transactions Monitoring and alerting False positives and false negatives System reliability and disaster recovery System Design Interview Topics We also discuss how to approach a Fraud Detection System Design Interview, including requirements gathering, API design, high-level architecture, data flow, database choices, scalability, consistency, availability, and trade-offs. If you're preparing for System Design Interviews, make sure to understand not just the architecture, but also why each component is used and what trade-offs it introduces. 👍 Like the video if you found it useful and subscribe for more System Design, Distributed Systems, Backend Engineering, and Architecture videos. #FraudDetection #SystemDesign #SystemDesignInterview #SoftwareArchitecture #DistributedSystems #Kafka #MachineLearning #BackendEngineering #SystemDesignInterviewQuestions