Abstract: One or more portions of a text corpus indicative of operational risk from a set of risk assessment documents is identified. Contextual features from the one or more portions of the text corpus are determined by applying a natural language processing (NLP) algorithm on the one or more portions. Risk identifiers are extracted based on the determined contextual features. A risk assessment software is generated based on the extracted risk identifiers and an operational risk category.

Abstract: A method, system, and computer program product for preprocessing raw data based on risk identifier tags are presented. A first set of risk identifier tags based on risk assessment data is generated, in which the risk assessment data includes a set of indicators of operational risk of an entity. At least one risk identifier tag of the first set of risk identifier tags matches content of a data item within a raw dataset is determined. The at least one risk identifier tag is mapped to the data item. The mapped data item is provided to a risk assessment system to determine operational risk rating of the entity.

Abstract: A method, in a data processing system comprising a processor and a memory, for analyzing product impact, the method comprising receiving, by the data processing system, data representative of an entity's operations, receiving, by the data processing system, a selection of one or more products, parsing, by the data processing system, features of the one or more products from product data input, and generating, by the data processing system, product profiles for the one or more products based on the parsed features. The method further comprising generating, by the data processing system, risk assessment data based on the data representative of the entity's operations and the product profiles, the risk assessment data including an indication of one or more changes in risk metrics of one or more risk components associated with the entity's operations by offering the one or more products.

Abstract: Document schemas for a first document from a first data source and a second document from a second source are identified. The document schema includes a set of tags and data elements corresponding to the set of tags. Based on the identified document schema, the set of tags of the first document to the set of tags of the second document are mapped. Portion of the first document is formatted based on the mapped set of tags. The formatted portion of the first document is positioned parallel to corresponding portion of the second document. The formatted first document and the second document are merged then displayed on the computer device.

Abstract: A method, in a data processing system comprising a processor and a memory, for analyzing domain-specific features, the method comprising receiving a selection of a domain from a client device, ingesting domain data from a data server, extracting domain elements from the domain data that correspond to the selected domain, and retrieving actionable information for the selected domain by using natural language processing and machine learning on the extracted domain elements and determining that the actionable information corresponds to the selected domain, the actionable information comprising operating parameters for the selected domain.

Abstract: A method, in a data processing system comprising a processor and a memory, for analyzing product impact, the method comprising receiving, by the data processing system, data representative of an entity's operations, receiving, by the data processing system, a selection of one or more products, parsing, by the data processing system, features of the one or more products from product data input, and generating, by the data processing system, product profiles for the one or more products based on the parsed features. The method further comprising generating, by the data processing system, risk assessment data based on the data representative of the entity's operations and the product profiles, the risk assessment data including an indication of one or more changes in risk metrics of one or more risk components associated with the entity's operations by offering the one or more products.

Abstract: A method and system that includes a data processing system comprising a processor, a memory and an artificial intelligence unit for retrieving information using a knowledge representation. The method comprising receiving, by the data processing system, a selection of a product from a computing device, parsing, by the data processing system, features of the product from product data input, generating, by the data processing system, queries from the parsed features, determining, by the data processing system, candidate answers for the queries, identifying, by the data processing system, requirements for the product based on the candidate answers, and providing, by the data processing system, the requirements to the computing device.

Abstract: A method, system, and computer program product for preprocessing raw data based on risk identifier tags are presented. A first set of risk identifier tags based on risk assessment data is generated, in which the risk assessment data includes a set of indicators of operational risk of an entity. At least one risk identifier tag of the first set of risk identifier tags matches content of a data item within a raw dataset is determined. The at least one risk identifier tag is mapped to the data item. The mapped data item is provided to a risk assessment system to determine operational risk rating of the entity.

Abstract: A protocol user interface (UI) element on a graphical user interface is generated, in which the protocol UI element includes an input field and is assigned with a weight value. The weight value is determined at least based upon data entered into the input field of the protocol UI element. The weight value assigned to the protocol UI element is adjusted based on historical event data associated with a protocol corresponding to the protocol UI element. Data entered into the input field of the protocol UI element is parsed. A risk assessment score based on the adjusted weight value and parsed data is dynamically calculated, in which the risk assessment score indicates a likelihood that an adverse event will occur as a result of violating the protocol.

Abstract: One or more portions of a text corpus indicative of operational risk from a set of risk assessment documents is identified. Contextual features from the one or more portions of the text corpus are determined by applying a natural language processing (NLP) algorithm on the one or more portions. Risk identifiers are extracted based on the determined contextual features. A risk assessment software is generated based on the extracted risk identifiers and an operational risk category.

Abstract: Document schemas for a first document from a first data source and a second document from a second source are identified. The document schema includes a set of tags and data elements corresponding to the set of tags. Based on the identified document schema, the set of tags of the first document to the set of tags of the second document are mapped. Portion of the first document is formatted based on the mapped set of tags. The formatted portion of the first document is positioned parallel to corresponding portion of the second document. The formatted first document and the second document are merged then displayed on the computer device.