We create knowledge and build services from data that enable enterprise wide data-driven decision making through science and applied research.
Systematically estimating the risk of a potential policy holder is a fundamental problem in the life insurance industry. Using data spanning nearly two decades and representing the health, behavioral preferences, and financial habits of millions of individuals, we are buliding state of the art algorithms and predictive models of risk. The results of this work stand to improve business efficiency and customer experience by providing a sound methodology and mechanism for accurately and nearly instantaneously estimating life insurance risk.
Many groups within MassMutual spend countless hours manually summarizing data sets and preparing reports delivered to company officers. This time-consuming process leaves little room for analysis. We develop interactive, web-based visualizations that connect to real-time data feeds, automatically producing statistically rich reports. These tools also provide unprecedented access to high-dimensional data that enables business analysts to generate actionable insights. We are currently building such a system for company-wide travel and entertainment financial expenses.
When a sales organization is resource constrained, how should they select which opportunities to prioritize? Using a data set spanning decades and containing thousands of historical sales opportunities and outcomes generated by a diverse set of sales representatives and financial agents, statistical models are used to identify which combinations of agents, sales representatives, and opportunity characterics lead to successful outcomes. A web-based tool based of this model is currently being used in an experiment with sales personnel to measure what effect the decision support tool has on sales outcomes.