- Industry: Finance
- Use Case: Banks and financial institutions use Flink to detect fraudulent transactions in real time. Flink processes streams of transactions, applying machine learning models and complex event processing (CEP) patterns to identify potentially fraudulent activities. If a suspicious transaction is detected, it can be flagged or blocked immediately.
- Example: A credit card company monitors transactions across millions of accounts to detect anomalies that might indicate fraud, such as unusual spending patterns or transactions from unfamiliar locations.
Alibaba
Alibaba uses Apache Flink to monitor and analyze real-time transaction data for fraud detection across its e-commerce platforms. By processing billions of transactions, Flink helps Alibaba detect fraudulent activities quickly and accurately, protecting customers and reducing financial losses.