Abstract: Embodiments disclosed herein disclose a back-end computer to generate a risk score and a front-end visualization engine to hierarchically display the generated risk core. The back-end computer users a machine learning model for a stepwise perturbation from a digital reference profile until a user profile to be score is reached. The computer may calculate intermediate risk score for each perturbation and calculate the final risk score after all the perturbations are completed. The front-end visualization engine generates an interactive hierarchical display showing information associated with the risk score calculation. More specifically, the visualization engine may show a filtered list of users sharing one or more attributes with the user profile, a visual rendering of the top factors contributing to the risk score, and individual input values within a factor; and juxtapose the scores and attributes of the user profile in the graphical information display of the associated population.

Abstract: Systems and methods for collecting and aggregating data from multiple data sources on a real-time basis in an organized manner that can be stored, distributed, published, analyzed, and retrieved in various different formats and for different purposes is described. The methods include providing a user with reports and insights created by consolidating all data records and activity into a single data record generated by a common data model.

Abstract: Embodiments disclosed herein disclose a back-end computer to generate a risk score and a front-end visualization engine to hierarchically display the generated risk core. The back-end computer users a machine learning model for a stepwise perturbation from a digital reference profile until a user profile to be score is reached. The computer may calculate intermediate risk score for each perturbation and calculate the final risk score after all the perturbations are completed. The front-end visualization engine generates an interactive hierarchical display showing information associated with the risk score calculation. More specifically, the visualization engine may show a filtered list of users sharing one or more attributes with the user profile, a visual rendering of the top factors contributing to the risk score, and individual input values within a factor; and juxtapose the scores and attributes of the user profile in the graphical information display of the associated population.