TitAnt: Online Real-time Transaction Fraud Detection in Ant Financial
This addresses the critical need for real-time fraud detection in e-commerce and e-payment systems, but it appears incremental as it focuses on deploying an existing or hybrid method in a specific domain.
The paper tackles the problem of detecting online transaction fraud in real time for Fintech businesses, introducing the TitAnt system deployed at Ant Financial, which predicts fraud in milliseconds and demonstrates effectiveness through extensive experiments on large real-world data.
With the explosive growth of e-commerce and the booming of e-payment, detecting online transaction fraud in real time has become increasingly important to Fintech business. To tackle this problem, we introduce the TitAnt, a transaction fraud detection system deployed in Ant Financial, one of the largest Fintech companies in the world. The system is able to predict online real-time transaction fraud in mere milliseconds. We present the problem definition, feature extraction, detection methods, implementation and deployment of the system, as well as empirical effectiveness. Extensive experiments have been conducted on large real-world transaction data to show the effectiveness and the efficiency of the proposed system.