Abstract: A system receives a speech of a user that indicates a request. The system extracts a plurality of voice features from the speech. The system converts the speech into a plurality of binary digits. The system determines a first voice feature constant value associated with a first voice feature, where the first voice feature constant value is an average of the first voice feature. The system determines a second voice feature constant value associated with the second voice feature, where the second voice feature constant value is an average of the second voice feature. The system encrypts the plurality of binary digits using the first and second voice feature constant values, where the encrypted plurality of binary digits corresponds to a voice-based hash value. The system generates a new block in a blockchain network using the voice-based hash value.

Abstract: A system for resolving exceptions in requests determines that a request comprises an exception. The exception impeded processing the request to be granted or denied. The system determines a type of exception that indicates whether the exception is incomplete information, incorrect information, or previously-unknown information. The system generates a block in a blockchain network. Based on the stored details in the block, the type of exception is identified. Accordingly, the block is segregated for exception processing based on its exception type. The system stores the exception in the block. The system compares the request with user information previously provided by the user. The system determines a similarity score between the request and the user information. The system compares the similarity score with a threshold percentage. In response to determining that the similarity score exceeds the threshold percentage, the system determines that the exception can be resolved and resolves the exception.

Abstract: Aspects of the disclosure relate to cognitive identification of credit reporting disputes and dispute resolution using quantum computing. A computing platform may retrieve, using a quantum computing device, dispute data from a block chain of dispute requests. The computing platform may convert the dispute data into quantum bits. The computing platform may perform quantum searching of the retrieved dispute data over a plurality of different databases and identify potential dispute transactions. The computing platform may determine probability scores for the potential dispute transactions, each probability score being based on a likelihood that a change associated with the potential dispute transactions is to be made. The computing platform may determine respective parameters associated with the potential dispute transactions, wherein each parameter indicates a type of change to be made.

Abstract: Aspects of the disclosure relate to cognitive identification of credit reporting disputes and dispute resolution using quantum computing. A computing platform may retrieve historical data and current credit report data and identify, using a DNA computing engine, potential reporting inaccuracies. The computing platform may send a recommendation to a computing device of a user to initiate a dispute. Based on receiving input from the user accepting the recommendation, the computing platform may initiate the dispute as a block in a distributed ledger. The computing platform may determine a probability that actual reporting inaccuracies exist. The computing platform may identify parameters for adjustment. In addition, each parameter may indicate a type of change to be made. The computing platform may update an account of the user based on the determined probability and the identified parameters. The computing platform may send a notification to the user indicating a resolution of the dispute.

Abstract: A system for validating a response based on context information receives a first message that indicates that a data object is removed from a memory resource via a third party device without authorization by a user. The system communicates a second response that indicates whether a third party confirms the removal of the data object without the authorization by the user to the third party device. The system receives a response from the third party device. The system extracts context information from the response. The system determines whether the response is valid based on the context information, where it is determined to be valid if the response is actionable. In response to determining that the response is actionable, the system recommends one or more actions to be performed with respect to the memory resource.

Abstract: A system splits the text into at least a first and a second portions. The system extracts a first context information from the first portion, and a second context information from a second portion in response to feeding the plurality of portions to a first plurality of neuron logic gates. The system compares the first context information with the second context information. If it is determined that the first context information is different from the second context information, the system dynamically activates at least one of a second plurality of neuron logic gates. The system determines an additional information from at least one of the first portion and second portions. The system updates at least one of the first context information and the second context information to include the additional information. The system generates a first output that comprises the updated first context information and the updated second context information.

Abstract: The systems and methods described include the ability to store resource transaction information in an immutable and distributed, verifiable fashion. The system includes enhanced means for retrieving, interacting with, and visualizing such information via user interface on a variety of user device types utilizing multiple information communication channels. The system is further configured to intelligently extract and analyze data to provide dispute identification information to an end user and further determine appropriate resolution actions based on historical data and extrapolated pattern identification.