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MONEY LAUNDERING, CORRUPTION AND GROWTH: AN EMPIRICAL RATIONALE FOR A GLOBAL CONVERGENCE ON ANTI-MONEY LAUNDERING REGULATION [PDF]
André Luiz Rossi de Oliveira +2 more
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Predictive Power of Random Forests in Analyzing Risk Management in Islamic Banking
, 2023 Aysan AF, Ciftler BS, Unal IM.
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Exploring predictive models to improve the accuracy of Housing Price Index forecasts in India's real estate sector. [PDF]
PLoS OneSingh N, Shanmugam K.
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A survey of deep learning applications in cryptocurrency. [PDF]
iScienceZhang J, Cai K, Wen J.
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Untangling the corruption maze: exploring the complexity of corruption in the health sector. [PDF]
Health Econ RevSommersguter-Reichmann M, Reichmann G.
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Stigmatisation of gambling disorder in social media: a tailored deep learning approach for YouTube comments. [PDF]
Harm Reduct JSinger J.
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Intelligent Anti-Money Laundering System
2006 IEEE International Conference on Service Operations and Logistics, and Informatics, 2006Criminal elements in today's technology-driven society are using every means available at their disposal to launder the proceeds from their illegal activities. While many anti-money laundering solutions have been in place for some time within the financial community, they cannot adapt to the ever-changing risk and methods in relation to money ...
Shijia Gao +3 more
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Legalization of Anti-Money Laundering
2014This first case study of self-regulatory impact on international legalization deals with international rules aimed at countering money laundering that began to emerge in the late 1980s when AML was primarily seen as a tool in the international but US-led fight against drugs Qakobi 2010b).
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