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Different methods can be used for this complex task. Most of them use machine learning, deep and neural networks. Usually, one big problem is working with imbalanced datasets. Some algorithms such as Smote and Adasyn could resolve the data skewness. One very important aspect of fraud detection is model explainability and rule extraction from the trained model.
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