Abstract: Systems and methods of processing a query from a user. A method includes receiving, by a server computer, an initial question from a client computer. The initial question includes a plurality of words and the server computer can identify a set of words in the plurality of words. Then the server computer can determine a list of clarifying questions based on a subset of the set of words. The server computer presents the list of clarifying questions to the client computer and receiving clarifying answers to the clarifying questions. The server computer determines an answer to the initial question and presents the answer to the client computer.

Abstract: An account holder's portfolio of transactions may be represented as a network of interconnected transaction nodes where each node represents a credit card transaction. This network may then be analyzed using artificial intelligence and machine learning techniques coupled with visual representations of the interrelated nodes to draw conclusions. An account holder or other system entity may report a fraudulent transaction that employs the holder's account information. A backend system may organize transaction information as a network of data nodes that includes a variety of interrelated information. The backend system may then identify all financial transaction “nodes” within the network that are related or connected by common data. For example, multiple transactions may include a common merchant as the reported fraudulent transaction. The backend may then perform an analysis of the nodes to identify likely fraudulent transactions based on one or more of the data elements for each node.

Abstract: An account holder's portfolio of transactions may be represented as a network of interconnected transaction nodes where each node represents a credit card transaction. This network may then be analyzed using artificial intelligence and machine learning techniques coupled with visual representations of the interrelated nodes to draw conclusions. An account holder or other system entity may report a fraudulent transaction that employs the holder's account information. A backend system may organize transaction information as a network of data nodes that includes a variety of interrelated information. The backend system may then identify all financial transaction “nodes” within the network that are related or connected by common data. For example, multiple transactions may include a common merchant as the reported fraudulent transaction. The backend may then perform an analysis of the nodes to identify likely fraudulent transactions based on one or more of the data elements for each node.

Abstract: Systems and methods of processing a query from a user. A method includes receiving, by a server computer, an initial question from a client computer. The initial question includes a plurality of words and the server computer can identify a set of words in the plurality of words. Then the server computer can determine a list of clarifying questions based on a subset of the set of words. The server computer presents the list of clarifying questions to the client computer and receiving clarifying answers to the clarifying questions. The server computer determines an answer to the initial question and presents the answer to the client computer.

Abstract: An account holder's portfolio of transactions may be represented as a network of interconnected transaction nodes where each node represents a credit card transaction. This network may then be analyzed using artificial intelligence and machine learning techniques coupled with visual representations of the interrelated nodes to draw conclusions. An account holder or other system entity may report a fraudulent transaction that employs the holder's account information. A backend system may organize transaction information as a network of data nodes that includes a variety of interrelated information. The backend system may then identify all financial transaction “nodes” within the network that are related or connected by common data. For example, multiple transactions may include a common merchant as the reported fraudulent transaction. The backend may then perform an analysis of the nodes to identify likely fraudulent transactions based on one or more of the data elements for each node.

Abstract: An ethylene polymer composition having improved optical properties and masterbatch for producing the composition comprising a predetermined amount of clarifying agent, and a predetermined amount of an amide slip agent.

Abstract: An ethylene polymer composition having improved optical properties and masterbatch for producing the composition comprising a predetermined amount of clarifying agent, and a predetermined amount of an amide slip agent.