🤖 machine learning
Application of Artificial Intelligence for Fraudulent Banking Operations Recognition
This study proposes and evaluates machine learning models, including logistic regression and stacked generalization, to effectively detect fraudulent banking transactions in the post-pandemic digital landscape, achieving a maximum AUC of 0.954 through advanced data preprocessing and feature engineering techniques.
Original paper licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer
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