What is the primary purpose of predictive modeling in retirement plans?

The primary purpose of predictive modeling in retirement plans is to assess health risks and cost drivers. This approach allows organizations to use historical data and statistical algorithms to identify patterns and predict future outcomes related to health care expenses and participation in retirement plans. By understanding these trends, plan sponsors can make informed decisions regarding plan design, funding, and the overall management of health-related costs for participants.

In the context of retirement plans, predictive modeling helps identify which factors most significantly affect costs and health outcomes, enabling better resource allocation and strategic planning. This data-driven insight supports not only the sustainability of the plan but also helps to improve outcomes for participants by identifying at-risk groups who may benefit from targeted interventions.

The other choices, while they may relate to different aspects of organizational management, do not align with the primary objectives of predictive modeling in the specific context of retirement plans. Enhancing marketing strategies and evaluating investment options are more aligned with financial and promotional initiatives rather than the risk and health assessment focus of predictive modeling. Decreasing manager fees pertains to cost management but does not directly involve the predictive analysis of participant health risks and related expenditures.