[Launching-ML System Design Tech Case Study Pulse #1]Handling Billions of Transaction Daily : How Amazon Efficiently Prevents Fraudulent Transactions (How it Actually Works)

Behind the tech with detailed explanation and flow chart....

Hi All,

Amazon's fraud detection system is a sophisticated machine learning infrastructure designed to identify and block suspicious activities across billions of transactions.

Let's explore the key metrics and capabilities of this system:

Key Metrics:

• Daily Active Users (DAU): 300+ million

• Transactions processed daily: 50+ million

• Peak requests per second: 1 million+

• Average fraud detection time: < 200ms

• ML model inference time: < 30ms

• Data points processed daily: 10+ trillion

• Global data centers: 20+

• Edge locations: 200+

• System availability: 99.999%

• False positive rate: < 0.05%

• Fraud detection rate: > 99.7%

• Features considered per transaction: 10,000+

• Model training datasets: Petabytes of historical transaction data

• ML models in production: 500+

• Real-time fraud alerts: Millions per day

• System redundancy: N+2 architecture

• Average model update cycle: 12 hours

Complete Process Flow: How It Works

The entire fraud detection process operates as a continuous pipeline from transaction initiation to final resolution:

1. User initiates a transaction on Amazon:

   • The client-side SDK captures transaction details and user context

   • Device fingerprinting collects hardware and behavioral signatures

   • The SDK establishes a secure connection with Amazon's servers

   • Transaction data is encrypted and sent to the Real-time Transaction Processing Service

   How it works: When a user clicks "Buy Now" or "Place Order," the Amazon mobile app or website silently activates the FraudShield SDK. This SDK collects over 300 device parameters including screen resolution, installed fonts, browser plugins, accelerometer readings, and network characteristics. This creates a device fingerprint that's extremely difficult to spoof. The SDK then uses TLS 1.3 with certificate pinning to establish a secure channel to Amazon's edge servers, encrypting all transaction data with AES-256.

2. Real-time Transaction Processing Service handles the incoming request:

   

   • Decrypts and validates the transaction data

   • Enriches the transaction with historical user data

   • Generates a unique transaction ID for tracking

   • Routes the request to the Fraud Detection Service

   How it works: The Transaction Processing Service operates as a distributed