Abstract: A system and method for detecting non-compliances using machine learning uses anomaly detection on an input dataset of unlabeled observations to produce output observations with corresponding probability scores of the output observations being anomalous. A portion of the output observations are labeled as being compliant observations based on the corresponding probability scores, which are added to a training dataset of compliant and non-compliant observations to derive an augmented dataset of compliant and non-compliant observations. The augmented dataset of compliant and non-compliant observations is then used to train a machine learning model for non-compliance detection.

Abstract: A processing platform is configured to maintain a plurality of reporting templates in the form of respective data structures, each of the data structures comprising a first field indicative of whether or not the corresponding template is a dynamic template and a plurality of additional fields comprising respective presentation unit identifiers having respective assigned values. The processing platform receives input data, and identifies at least one of the reporting templates that is relevant to the input data. For an identified reporting templates that is a dynamic template, the processing platform generates report presentation output in which presentation units corresponding to respective ones of the presentation unit identifiers are generated based at least in part on respective portions of the input data. The processing platform delivers the report presentation output to at least one of client device over a network.

Abstract: A processing platform is configured to maintain a plurality of reporting templates in the form of respective data structures, each of the data structures comprising a first field indicative of whether or not the corresponding template is a dynamic template and a plurality of additional fields comprising respective presentation unit identifiers having respective assigned values. The processing platform receives input data, and identifies at least one of the reporting templates that is relevant to the input data. For an identified reporting templates that is a dynamic template, the processing platform generates report presentation output in which presentation units corresponding to respective ones of the presentation unit identifiers are generated based at least in part on respective portions of the input data. The processing platform delivers the report presentation output to at least one of client device over a network.