Systems and methods for interactive annuity product services using machine learning modeling

A system comprising:

• a server computing device communicably coupled to a database computing device and having a machine learning processor programmed with an instruction to execute
• an artificial intelligence algorithm, the server computing device programmed to:
• generate an input data set by:
• determining a set of user information associated with a user, including user demographics, user risk preferences, and user objectives;
• determining a set of market index information, including historical market index information, current market index information, and forecast market index information;
• and
• determining one or more available annuity products using the set of user information;
• execute, by the machine learning processor, a price optimization module to traverse a computer-generated annuity matching model using the input data set to select a subset of the available annuity products that are associated with product characteristics that match one or more of the user objectives and generate one or more annuity product recommendations for the user based upon the subset of annuity products;
• and
• execute, by the machine learning processor, a market simulation module to traverse a computer-generated annuity performance prediction model using the subset of annuity products selected by the price optimization module and one or more predictions of market performance, the market simulation module generating one or more simulated outcomes for
• each of the annuity products in the subset of annuity products;
• the system further comprising a client computing device communicably coupled to the server computing device, the client computing device configured to:
• generate a graphical user interface for display to the user via a display device, the graphical user interface including one or more visual representations of each of:
• the one or more annuity product recommendations and the one or more simulated outcomes,
• wherein the machine learning processor and the modules execute the artificial intelligence algorithm to improve the computer-generated models by automatically assimilating newly-collected input data elements from an external data source into the computer-generated models without relying on manual intervention, and
• wherein the server computing device further configured to build, by the machine learning processor, the computer-generated annuity matching model by training a machine learning algorithm programmed on the machine learning processor against a training data set.