Nowadays, identity theft has become a huge problem for many industries. Published in FTC1’s 2019 data book, there were 650,572 cases of identity theft in 2019. Among identity theft, credit card fraud is the most common type of fraud. At the end of July 2020, the Federal Trade Commission had fielded almost 150,000 COVID-19 and stimulus-related fraud reports in 2020.
There are two modes of identity fraud:
- The first type is that someone gets a list of identities (maybe stolen or bought on the internet) and combines them with his or her own contact information such as address and phone number to make up fake identities.
- The second type is that someone’s identity is compromised in a data breach which leads to his or her identity information being used by many identity thefts.
This report will go through how we examine a credit card and cell phone application dataset and how we attempt to build a supervised learning model to identify real-time application fraud. We used Python to conduct all the analysis.
Team member:Jiaqin Lu, Li Huang, Yifan Shi, Yiqi Yang, Yimi Li, Yuan Xin