Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Faculty of Business | en_US |
| dc.contributor.advisor | Xu, Xin (MM) | en_US |
| dc.contributor.advisor | Ng, Ka Chung Boris (MM) | en_US |
| dc.creator | Liu, Yi | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/13690 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | en_US |
| dc.rights | All rights reserved | en_US |
| dc.title | The study of FinTech solutions to help anti-fraud in social media and e-commerce business | en_US |
| dcterms.abstract | Telecom and online fraud have become a nightmare for countless people in recent years, with practitioners in telecom and online fraud groups using social media and e-commerce platforms to cover up their illegal activities. The existing anti-telecom and online fraud systems of public security agencies have partially resolved the verification and blocking processes for remittance routes related to fraud-related funds, but these measures are costly and not very timely. In the anti-telecom and online fraud scenario, there exists an "impossible triangle" mechanism where "cost of solutions", "convenience of financial technology" and “quality of anti-telecom and online fraud methods" cannot coexist. I use data-drive methods to design and develop a large language model based recommendation model for vulnerable victims. I successfully implement a working system that generates early warnings of black bank card to help recover funds from fraud. This is called “Stop payment mechanism”, allowing only deposits but no withdrawals. I also implement a working system that can find black sim card to help internet platforms identify fraud accounts. Ultimately, my system has proven to be highly effective in fraud prevention with minimal cost and without significantly impacting the convenience of financial technology. | en_US |
| dcterms.extent | xi, 174 pages : color illustrations | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2025 | en_US |
| dcterms.educationalLevel | DFinTech | en_US |
| dcterms.educationalLevel | All Doctorate | en_US |
| dcterms.LCSH | Internet fraud -- Prevention | en_US |
| dcterms.LCSH | Computer fraud -- Prevention | en_US |
| dcterms.LCSH | Hong Kong Polytechnic University -- Dissertations | en_US |
| dcterms.accessRights | restricted access | en_US |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 8214.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 4.08 MB | Adobe PDF | View/Open |
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