Fraud Detection – ML System Design Interview

MasterCard, Visa, Paypal and Revolut all use fraud detection systems design question for their AI/ML roles. Fraud detection is a critical application of machine learning, helping businesses prevent financial losses . In this video, we break down the ML system design process for building a scalable, efficient, and real-time fraud detection system suitable for FAANG interviews.

💡 What You’ll Learn:
✅ Key components of an ML-based fraud detection system
✅ Feature engineering & anomaly detection techniques
✅ Model selection: Unsupervised learning
✅ Deployment challenges & best practices

🚀 Whether you’re a data scientist, ML engineer, or fintech professional, this video will give you practical insights to design robust fraud detection models.

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Chapters:
00:00 Introduction
00:10 The Question
00:55 Target Architecture
01:30 Requirements
03:23 Data Collection
04:40 Data Security
05:15 Data Collection 2
05:30 Feature Engineering
07:30 ML Model & Training
11:30 Model Serving API
13:20 Real Time Feedback
14:00 Performance Tracking

#interview #code #ai #machinelearning

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