Classification-Based Fraud Detection for Payment Marketing and Promotion
Shuo He1,∗, Jianbin Zheng1,†, Jiale Lin2,‡, Tao Tang1,§, Jintao Zhao1,¶, Hongbao Liu1,ll
Computer Systems Science and Engineering, Vol.35, No.3, pp. 141-149, 2020, DOI:10.32604/csse.2020.35.141
Abstract Nowadays, many payment service providers use the discounts and other marketing strategies to promote their products. This also raises the issue of people
who deliberately take advantage of such promotions to reap financial benefits. These people are known as ‘scalper parties’ or ‘econnoisseurs’ which can
constitute an underground industry. In this paper, we show how to use machine learning to assist in identifying abnormal scalper transactions. Moreover,
we introduce the basic methods of Decision Tree and Boosting Tree, and show how these classification methods can be applied in the detection of abnormal
transactions. In addition,… More >