Abstract: Systems and methods for processing items in a queue, a system including one or more memory devices storing instructions and one or more processors configured to execute the instructions to perform operations including: analyzing training data to build a predictive model; applying the predictive model to items in a queue to determine scores of the items based on respective probabilities of an entity completing an action for each item; listing the items, sorted by the scores, in a first display view; identifying a first and a second item, respectively having highest and next highest scores; grouping, with each of the first and second items, items that satisfy a grouping condition based on characteristic information of the items; and listing the groups of items including the first and second items, sorted based on the scores of the first and second items, in a second display view.

Abstract: Disclosed herein are system, method, and computer program product embodiments for generating optimized data structure objects. In a given embodiment, a server receives a request to identify a set of data structure objects from a plurality of data structure objects for a specified vehicle and a specified user and based on user objective data and an attribute. The server may generate the plurality of data structure objects within constraints of the user objective data, policy data, and the attribute. The server may identify the set of data structure objects from the plurality of data structure objects. Each data structure object of the set is within a threshold distance to a value of at least one dimension of a set of the dimensions of the set of dimensions of a model.

Abstract: Systems and methods for processing items in a queue, a system including one or more memory devices storing instructions and one or more processors configured to execute the instructions to perform operations including: analyzing training data to build a predictive model; applying the predictive model to items in a queue to determine scores of the items based on respective probabilities of an entity completing an action for each item; listing the items, sorted by the scores, in a first display view; identifying a first and a second item, respectively having highest and next highest scores; grouping, with each of the first and second items, items that satisfy a grouping condition based on characteristic information of the items; and listing the groups of items including the first and second items, sorted based on the scores of the first and second items, in a second display view.

Abstract: Systems and methods for optimizing processing of loan applications are disclosed. A system may include one or more memory devices storing instructions and one or more processors configured to execute the instructions. The instructions may instruct the system to analyze training data to build a predictive model. The instructions may also instruct the system to apply the predictive model to a loan application to determine a first probability of an institution funding the loan application if the institution proactively engages a loan-arranging entity of the loan application and a second probability of the institution funding the loan application if the institution reactively engages the loan-arranging entity. The instructions may further instruct the system to reporting the first and second probabilities to a user through a user interface.

Abstract: Systems and methods for processing items in a queue, a system including one or more memory devices storing instructions and one or more processors configured to execute the instructions to perform operations including: analyzing training data to build a predictive model; applying the predictive model to items in a queue to determine scores of the items based on respective probabilities of an entity completing an action for each item; listing the items, sorted by the scores, in a first display view; identifying a first and a second item, respectively having highest and next highest scores; grouping, with each of the first and second items, items that satisfy a grouping condition based on characteristic information of the items; and listing the groups of items including the first and second items, sorted based on the scores of the first and second items, in a second display view.

Abstract: Systems and methods for processing items in a queue, a system including one or more memory devices storing instructions and one or more processors configured to execute the instructions to perform operations including: analyzing training data to build a predictive model; applying the predictive model to items in a queue to determine scores of the items based on respective probabilities of an entity completing an action for each item; listing the items, sorted by the scores, in a first display view; identifying a first and a second item, respectively having highest and next highest scores; grouping, with each of the first and second items, items that satisfy a grouping condition based on characteristic information of the items; and listing the groups of items including the first and second items, sorted based on the scores of the first and second items, in a second display view.

Abstract: Systems and methods for optimizing processing of loan applications are disclosed. A system may include one or more memory devices storing instructions and one or more processors configured to execute the instructions. The instructions may instruct the system to analyze training data to build a predictive model. The instructions may also instruct the system to apply the predictive model to a loan application to determine a first probability of an institution funding the loan application if the institution proactively engages a loan-arranging entity of the loan application and a second probability of the institution funding the loan application if the institution reactively engages the loan-arranging entity. The instructions may further instruct the system to reporting the first and second probabilities to a user through a user interface.

Abstract: Systems and methods for optimizing processing of loan applications are disclosed. A system may include one or more memory devices storing instructions and one or more processors configured to execute the instructions. The instructions may instruct the system to analyze training data to build a predictive model. The instructions may also instruct the system to apply the predictive model to a loan application to determine a first probability of an institution funding the loan application if the institution proactively engages a loan-arranging entity of the loan application and a second probability of the institution funding the loan application if the institution reactively engages the loan-arranging entity. The instructions may further instruct the system to reporting the first and second probabilities to a user through a user interface.

Abstract: Systems and methods for optimizing processing of loan applications are disclosed. A system may include one or more memory devices storing instructions and one or more processors configured to execute the instructions. The instructions may instruct the system to analyze training data to build a predictive model. The instructions may also instruct the system to apply the predictive model to a loan application to determine a first probability of an institution funding the loan application if the institution proactively engages a loan-arranging entity of the loan application and a second probability of the institution funding the loan application if the institution reactively engages the loan-arranging entity. The instructions may further instruct the system to reporting the first and second probabilities to a user through a user interface.