Abstract: Systems, methods, apparatuses, and computer program products for natural language processing to extract and classify text, and automatically identify information about an entity or institution, are provided. One method may include monitoring, by a computing device, a public network, and automatically ingesting, from the network, content comprising text. The method may also include extracting the text from the content and passing the extracted text as input to a classification model, which processes the text to generate a semantic vector representation of the text and compares the generated semantic vector representation with previously labeled vectors. The method may then include determining a prediction on a meaning of the text based on the result of the comparing step or based on a similarity of the generated vector to other grouped labels of stored vectors, and outputting the prediction of the meaning of the text.

Abstract: Systems, methods, apparatuses, and computer program products for evaluating and/or rating entities using machine learning techniques are provided. One method may include receiving, by a computer system, identifying information for an entity and collecting data relating to the entity from at least one of public data sources or private data sources. The method may further include determining and producing data that is actually relevant to the entity, and classifying the relevant data into different areas of risk associated with the entity. The method may also include using the relevant data, different areas of risk associated with the entity, and information regarding risk attributes of the entity to determine and assign, through an entity risk model, a risk score for the entity, and outputting the risk score for the entity to a device of an end user.