CSE498, Collaborative Design, Spring 2021
Computer Science and Engineering
Michigan State University

Founded in Bellevue, Washington in 1994, Amazon is a Fortune 500 company that provides a variety of services to customers and is the world’s largest cloud services provider and online retailer.

Amazon’s online marketplace handles millions of orders every day from over a million unique sellers. With an operation of such magnitude, it is inevitable that some buyers and even some sellers engage in fraudulent activities. Amazon’s current fraud detection system requires individual sellers to detect and recognize unusual activity themselves, which can lead to undetected fraud and extra work for sellers.

Our Sentinel system helps to resolve these issues by automatically detecting fraudulent transactions and notifying sellers in real time.

Sentinel uses machine learning to detect patterns from historical transaction data, then applies these patterns to all incoming transactions to determine when a fraudulent transaction has occurred. Once Sentinel has detected fraud, the seller is notified immediately.

Using our mobile application, sellers can manage all of their orders, including any fraud detected by Sentinel. Our application gives sellers options to freeze their account, cancel any fraudulent orders, or to explore more transactions before making a decision.

Sentinel helps Amazon sellers save time and money by detecting and mitigating fraudulent purchases automatically, giving sellers much needed peace of mind.

Our machine learning models are built using Amazon SageMaker, trained on user data and transactions stored in Amazon S3. AWS Lambda is used to detect instances of fraud in real time and the cloud platform sends a notification to the merchant’s mobile device. The iOS application is written in Swift.