English

TitAnt: Online Real-time Transaction Fraud Detection in Ant Financial

Machine Learning 2019-06-19 v1 Cryptography and Security Machine Learning

Abstract

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.

Keywords

Cite

@article{arxiv.1906.07407,
  title  = {TitAnt: Online Real-time Transaction Fraud Detection in Ant Financial},
  author = {Shaosheng Cao and Xinxing Yang and Cen Chen and Jun Zhou and Xiaolong Li and Yuan Qi},
  journal= {arXiv preprint arXiv:1906.07407},
  year   = {2019}
}