Analyzing Existing Patterns in Transactions for Terrorism Financing Detection
This study aims to enhance terrorism financing detection mechanisms by analyzing existing patterns in financial transactions. Utilizing advanced data analysis techniques and machine learning models, we identified significant transaction patterns indicative of terrorism financing activities. The proposed models demonstrated improved accuracy and efficiency over traditional detection methods. The findings have substantial implications for financial institutions and regulatory bodies in strengthening financial security and preventing illicit activities.
Authors
- Aigerim Bolshibayeva (ORCID: https://orcid.org/0000-0003-1191-4249)
- Aliya Kulbayeva (ORCID: https://orcid.org/0009-0002-7245-8312)
- Dinara Kozhamzharova (ORCID: https://orcid.org/0000-0002-4320-9774)
- Sabina Rakhmetulayeva (ORCID: https://orcid.org/0000-0003-4678-7964)
Institutions
- Satbayev University (KZ)
- International Information Technologies University (KZ)
Publication Details
- Published
- 2024-12-11
- DOI
- https://doi.org/10.1109/irc63610.2024.11053980
- Primary Topic
- Imbalanced Data Classification Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00