For fraud detection, AI is used to identify anomalies in transactions or customer behaviors, which may indicate potential fraud. Different technologies and techniques can be used for fraud detection, such as supervised and unsupervised machine learning, network analysis, and business rules. Combining several of these techniques and using current and appropriate data can improve the accuracy of the results. It is important to note that fraud detection can be a complex and evolving process.
Technologies To perform this classification or grouping, machine learning and deep learning models are used, which is why Python and several of its libraries are one of the best options.
Next Steps: Deploy the model and conduct further testing.