An Xgboost based system for financial fraud detection
Shimin Lei, Ke Xu, Huang Yizhe, Xinye Sha
Abstract
Credit card fraud leads to billions of losses in online transaction. Many corporations like Alibaba, Amazon and Paypal invest billions of dollars to build a safe transaction system. There are some studies in this area having tried to use machine learning or data mining to solve these problems. This paper proposed our fraud detection system for e- commerce merchant. Unlike many other works, this system combines manual and automatic classifications. This paper can inspire researchers and engineers to design and deploy online transaction systems.
Topics & Concepts
Credit card fraudDatabase transactionCredit cardTransaction dataComputer scienceComputer securityBusinessData scienceDatabaseWorld Wide WebPaymentImbalanced Data Classification TechniquesNetwork Security and Intrusion DetectionData Stream Mining Techniques