Credit scoring system for online shopping and loan companies
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 dif...
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| Other Authors: | |
| Format: | Final Year Project (FYP) |
| Language: | English |
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2019
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| Online Access: | http://hdl.handle.net/10356/77143 |
| _version_ | 1824454227235176448 |
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| author | Ng, Hwee Yuan |
| author2 | Nicolas Privault |
| author_facet | Nicolas Privault Ng, Hwee Yuan |
| author_sort | Ng, Hwee Yuan |
| collection | NTU |
| description | 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. |
| first_indexed | 2025-02-19T03:18:57Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/77143 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2025-02-19T03:18:57Z |
| publishDate | 2019 |
| record_format | dspace |
| spelling | ntu-10356/771432023-02-28T23:18:39Z Credit scoring system for online shopping and loan companies Ng, Hwee Yuan Nicolas Privault School of Physical and Mathematical Sciences DRNTU::Science::Mathematics 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. Bachelor of Science in Mathematical Sciences 2019-05-13T13:43:04Z 2019-05-13T13:43:04Z 2019 Final Year Project (FYP) http://hdl.handle.net/10356/77143 en 34 p. application/pdf |
| spellingShingle | DRNTU::Science::Mathematics Ng, Hwee Yuan Credit scoring system for online shopping and loan companies |
| title | Credit scoring system for online shopping and loan companies |
| title_full | Credit scoring system for online shopping and loan companies |
| title_fullStr | Credit scoring system for online shopping and loan companies |
| title_full_unstemmed | Credit scoring system for online shopping and loan companies |
| title_short | Credit scoring system for online shopping and loan companies |
| title_sort | credit scoring system for online shopping and loan companies |
| topic | DRNTU::Science::Mathematics |
| url | http://hdl.handle.net/10356/77143 |
| work_keys_str_mv | AT nghweeyuan creditscoringsystemforonlineshoppingandloancompanies |