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    Fighting Financial Crime: Anti-Money Laundering Strategies

    anti-money laundering
    virtual worlds
    Created at: 30-03-2023
    Last updated: 18-12-2023
    This playlist focuses on the critical topic of Anti-Money Laundering (AML) strategies that are essential in fighting financial crime. With expert insights, the playlist covers vari...
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    Sun Dec 17 2023

    Financial Fraud Mitigation using RF-XGBoost model


    Machine learning offers the ability to analyze large financial data and extract hidden knowledge for anomalous patterns. In the current study, we propose an ensemble machine learning framework using eXtreme Gradient Boosting (XGBoost) and random forest for the detection of financial frauds. The model used an adaptive synthetic (ADASYN) algorithm over sampling technique with out-of-bag scoring on a grid search algorithm for the 11 input features. We tested our framework which shows promising results over benchmark models.

    Andreas Karapatakis

    Sun Mar 26 2023

    Virtual worlds and money laundering under EU law: The inadequacy of the existing legal framework and the challenges of regulation


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