Abstract: A rule training system and methods are provided that are configured to generate machine learning rules for fraud detection based on an automated feature selection by a rule creation system. The system includes a processor and a computer readable medium operably coupled thereto, the computer readable medium comprising a plurality of instructions stored in association therewith that are accessible to, and executable by, the processor, to perform rule creation operations which include accessing a training dataset, performing a data preprocessing and a data sampling on the training dataset, obtaining a plurality of features from the processed and sampled dataset using a feature engineering operation, selecting a subset of features from the plurality of features using simulated annealing operations, generating the plurality of detection rules using the subset of features, iteratively selecting from the plurality of detection rules, and evaluating a rule performance of each rule in those selected.