Description: The insurance industry has a lot to learn from academia's missteps. With predictive analytics assuming an ever-expanding role in risk modeling, carriers would be well-served to establish practices that mitigate the creation of faulty models. Hear practical advice on how to mitigate the risks of overfitting, with a focus on how to translate complex policyholder behavior experience data for long-term products into behavioral models using company- and industry-level data.

Description: This session meets the needs of life insurance actuaries who are focused on experience studies, assumption setting, and/or product development. The presenters will use industry data to illustrate how policyholders react to product design, such as premium jumps in the PLT period and UL with high interest rate illustration, and trends in the life insurance market, including the introduction of smoking distinguished rates and the shift towards an increasing number of preferred underwriting classes.