Abstract: Systems and methods are described for analyzing user data, for instance for eligibility of a user for one or more programs. The user data is analyzed in two or more stages, with each stage including rules and/or program qualification criteria specific to that stage. In some examples, the systems and methods used trained machine learning models for at least one stage of the analysis. The systems and methods disclose identifying one or more programs that the user is eligible for, and in some cases, applying the one or more programs to the user's account.

Abstract: Systems and methods are described for analyzing user data, for instance for eligibility of a user for one or more programs. The user data is analyzed in two or more stages, with each stage including rules and/or program qualification criteria specific to that stage. In some examples, the systems and methods used trained machine learning models for at least one stage of the analysis. The systems and methods disclose identifying one or more programs that the user is eligible for, and in some cases, applying the one or more programs to the user's account.

Abstract: Qualification decisioning systems and techniques are described. For instance, a system receives user information that is indicative of a user's income stream and/or asset(s). The system receives product qualification criteria data corresponding to products, with different products corresponding to different product-specific qualification criteria. The product qualification criteria data can change over time. The system dynamically analyzes the user information and the product qualification criteria data using a trained machine learning (ML) model in real-time as the user information and the product qualification criteria data continue to be received. The trained ML model identifies a subset of the plurality of products that the user qualifies for at a specific time. The system outputs recommendations for the subset of the plurality of products.

Abstract: Systems and methods are described for analyzing user data, for instance for eligibility of a user for one or more programs. The user data is analyzed in two or more stages, with each stage including rules and/or program qualification criteria specific to that stage. In some examples, the systems and methods used trained machine learning models for at least one stage of the analysis. The systems and methods disclose identifying one or more programs that the user is eligible for, and in some cases, applying the one or more programs to the user's account.