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Eileen is an actuary in the Seattle Life insurance consulting practice of Milliman. She is associated with a cross-practice center of excellence in predictive analytics. She joined the firm in 2011.
Eileen specializes in predictive analytics. She managed Milliman's first industry level study of variable annuity policyholder lapse behavior using predictive modeling, published to participants in 2015. The study set the standard for data preparation and for presentation of predictive modeling results. In 2016 her team initiated a similar study on partial withdrawal behavior for variable annuity policyholders with guaranteed lifetime withdrawal benefits. The group has also completed several single-company studies on policyholder behavior for various products.
Eileen is a frequent speaker at industry meetings on topics associated with predictive analytics. Sessions have included describing the many possible mathematical forms that predictive modeling may encompass, defining what is needed to start using predictive modeling for assumption setting, explaining what to expect from a typical project, and describing how to leverage predictive models to inform stochastic liability projections.
Prior to Milliman, Eileen worked for six years at AXA Equitable in New York, NY. At AXA, she worked first in ceded and assumed reinsurance, and later in life insurance projections and earnings analysis, covering interest-sensitive and traditional products. Her duties included embedded value reporting, transitioning several models into MG-ALFA and maintaining them within a company-wide control structure, as well as preparing cash flow projections for a closed block securitization.
In the years between AXA Equitable and Milliman, Eileen obtained a master's degree in Quantitative Ecology and Resource Management. She specialized in mathematical optimization (a modeling technique commonly used in construction of replicating portfolios), with an application to allocation of conservation resources. She completed advanced coursework in theoretical and applied statistics, and is now applying that knowledge to advancing Milliman's expertise in predictive analytics.