Credit scoring system for online shopping and loan companies

• Main Author: Ng, Hwee Yuan
• Other Authors: Nicolas Privault
• Format: Final Year Project
• Language: English
• Published: 2019
• Subjects: DRNTU::Science::Mathematics
• Online Access: http://hdl.handle.net/10356/77143
• Institution: Nanyang Technological University

Till today, consumers and firms seek assistance from financial institutions whenever they are faced with any financial difficulties. For credit lenders, sometimes, it is difficult to gauge the borrower's credibility, especially for consumers. Therefore, in this thesis, in order to curb this difficulty, an alternative method using digital footprint (non-traditional data) will be considered along with various statistical methods to perform numerous analysis, using R. In this project, since actual data for non-traditional data is not readily available for use, data generation is required during the process. Lastly, results using different set of data will presented along with insights and implications as well.