Systems and methods for interactive annuity product services using machine learning modeling
Abstract:
A server computing device generates an input data set by determining a set of user information, a set of market index information, and available annuity products. A machine learning processor executes a price optimization module to traverse a computer-generated annuity matching model and select a subset of the available annuity products that are associated with product characteristics that match user objectives and generate annuity product recommendations for the user. The processor executes a market simulation module to traverse a computer-generated annuity perfor-mance prediction model using the annuity product recom-mendations and predictions of market performance to gen-erate simulated outcomes for each of the annuity products. A client device generates a graphical user interface for display to the user via a display device, the graphical user interface including visual representations of each of: the annuity product recommendations and the simulated out-comes.
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