Abstract: Aspects of the disclosure relate to intelligently aggregating data using a convolutional network quantum processor. Using an artificial intelligence model, a computing platform may identify dependencies derived from a consumer request and corresponding values. For each configuration of dependency and corresponding value, the computing platform may determine a likelihood of success. The computing platform may alter the configurations and may determine a likelihood of success for each altered configuration. The computing platform may train a convolutional network to analyze the consumer request using the configurations, the altered configurations, and/or corresponding likelihoods of success. The convolutional network may generate a function that describes the dependencies derived from the consumer request. Using a quantum processing model, the computing platform may analyze different states of the function in parallel and may determine whether to approve or deny the consumer request based on the analysis.

Abstract: Aspects of the disclosure relate to dynamic model configuration and execution. A computing platform may receive first model data comprising first model execution configuration data and first model output configuration data. The computing platform may generate a first model based on the first model execution configuration data. The computing platform may distribute, to a plurality of computing platforms, the first model, the first model execution configuration data, and the first model output configuration data. The computing platform may receive a second request to execute one or more models from a third computing platform. The computing platform may receive, from the third computing platform, first model execution data. The computing platform may execute the first model based on the first model execution data and the first model execution configuration data to generate a first model output score.

Abstract: A process orchestration and dynamic data acquisition system may allow process flows to be flexible and to customer or product requirements based on rules obtained from a rule management system. The process orchestrator may be driven based on an updatable and dynamic set of business rules to allow for quick changes to the process flow. Through the business rules the process orchestrator retrieves and processes data necessary to the process based on a customer request and/or product or service provided. The process orchestrator provides dynamic data aggregation from both internal and external data sources, through calling re-useable processes instantiated by the process host system and continuously adapts the process flow to meet the unique needs of each request input and results returned from each dynamic process call.

Abstract: Aspects of the disclosure relate to dynamic model configuration and execution. A computing platform may receive first model data comprising first model execution configuration data and first model output configuration data. The computing platform may generate a first model based on the first model execution configuration data. The computing platform may distribute, to a plurality of computing platforms, the first model, the first model execution configuration data, and the first model output configuration data. The computing platform may receive a second request to execute one or more models from a third computing platform. The computing platform may receive, from the third computing platform, first model execution data. The computing platform may execute the first model based on the first model execution data and the first model execution configuration data to generate a first model output score.

Abstract: A process orchestration and dynamic data acquisition system may allow process flows to be flexible and to customer or product requirements based on rules obtained from a rule management system. The process orchestrator may be driven based on an updatable and dynamic set of business rules to allow for quick changes to the process flow. Through the business rules the process orchestrator retrieves and processes data necessary to the process based on a customer request and/or product or service provided. The process orchestrator provides dynamic data aggregation from both internal and external data sources, through calling re-useable processes instantiated by the process host system and continuously adapts the process flow to meet the unique needs of each request input and results returned from each dynamic process call.

Abstract: Aspects of the disclosure relate to dynamic model configuration and execution. A computing platform may receive first model data comprising first model execution configuration data and first model output configuration data. The computing platform may generate a first model based on the first model execution configuration data. The computing platform may distribute, to a plurality of computing platforms, the first model, the first model execution configuration data, and the first model output configuration data. The computing platform may receive a second request to execute one or more models from a third computing platform. The computing platform may receive, from the third computing platform, first model execution data. The computing platform may execute the first model based on the first model execution data and the first model execution configuration data to generate a first model output score.

Abstract: Methods, systems, and computer-readable media for providing an integrated credit decision platform are presented. An integrated credit decision platform may integrate customer data across a variety of areas. For example, a customer may have a credit line, a checking account, a mortgage, or other suitable financial accounts with a financial institution. The integrated platform may make customer data across accounts available during a credit decision. In an embodiment, an organization, such as a financial institution, may receive a credit request from a customer. The credit request may include a request to change the status of the customer's credit with the financial institution. Integrated data may be accessed for the customer. For example, one or more of a checking account balance, a saving's account balance, and credit line, a payment history, and other suitable data may be accessed. A decision whether to grant or deny the customer's credit request may be based on the accessed integrated data.