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Financial fraud in the digital era requires advanced detection methods, and artificial intelligence, especially machine learning, has become essential for this purpose. Financial institutions across all sectors must develop their data evaluation competencies and analytical abilities because this lets them maximize their AI technology applications to recognize financial crimes before they occur and automate their fraud detection processes. Machine learning models, including logistic regression and decision trees, serve the industry routinely while data mining techniques validate their success in fighting credit card fraud. Advanced machine learning solutions are required to study and deploy new detection techniques that enable the detection of new sophisticated fraud techniques. Modern electronic commerce combined with international communication networks has provoked increasing fraudulent incidents, thus necessitating better fraud detection systems. New techniques provide means to improve both the precision and processing speed and comprehensive operational performance of systems that detect fraud.
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