Redefining anti-money laundering detection: the role of artificial intelligence in financial security
Vitale, Francesco (A.A. 2023/2024) Redefining anti-money laundering detection: the role of artificial intelligence in financial security. Tesi di Laurea in Artificial intelligence and machine learning, Luiss Guido Carli, relatore Giuseppe Francesco Italiano, pp. 62. [Bachelor's Degree Thesis]
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Abstract/Index
Motivation. Money laundering. Phases of money laundering. Theoretical background. Anti-money laundering (AML). General data protection regulation (GDPR). AML industry frameworks. Machine learning for AML. Fundamentals of machine learning in AML. General principles in ML. Machine learning algorithms in AML. Shortcomings of current AI models. Data. Exploratory data analysis (EDA). Data processing. Models implementation. Outlier detection. Risk scoring. Models comparison.
References
Bibliografia: pp. 59-61.
| Thesis Type: | Bachelor's Degree Thesis |
|---|---|
| Institution: | Luiss Guido Carli |
| Degree Program: | Bachelor's Degree Programs > Bachelor's Degree Program in Management and Computer Science, English language (L-18) |
| Chair: | Artificial intelligence and machine learning |
| Thesis Supervisor: | Italiano, Giuseppe Francesco |
| Academic Year: | 2023/2024 |
| Session: | Summer |
| Deposited by: | Alessandro Perfetti |
| Date Deposited: | 16 Oct 2024 13:54 |
| Last Modified: | 16 Oct 2024 13:54 |
| URI: | https://tesi.luiss.it/id/eprint/40045 |
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