AI in Financial Fraud Detection: A Comparative Analysis of Machine Learning Models
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Abstract
Financial fraud detection is a critical application of AI in the financial industry. This paper compares various machine learning models, including logistic regression, decision trees, and neural networks, for detecting fraudulent transactions. By evaluating these models on real-world data, we provide insights into their effectiveness and propose strategies for improving fraud detection accuracy.
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