Description: Volatile interest rates, repositioned investment portfolios, and stress in the banking sector are driving insurers to manage market risk and counterparty credit risk. Our experts in investments, derivatives, and hedge accounting will discuss this new market environment and its impact on hedging. The conversation will include practical case studies, including hedging future bond purchases, hedging floating-rate CLOs, and counterparty credit risk management.

Description: Hot topics and emerging trends in assumption development in US life insurance companies

Description: Explore insights to non-traditional actuarial roles from a panelist with experiences in data science, finance and entertainment. The panelist will be sharing their perspectives on their non-traditional actuarial role in relation to the actuarial profession.

Description: Are Accelerated Underwriting (AU) programs performing as expected? As mortality experience will (hopefully) be slow to emerge, it is pivotal that we look at alternative methods of monitoring early performance. From random hold outs, to post-issue APS's, and post-issue prescription profiles, explore popular monitoring techniques and lessons learned so far. Focus on confusion matrices that provide an early indication of mortality slippage relative to fluid-based underwriting decisions. Finally, explore statistical methods to determine what constitutes credibility and identify opportunities to think about mortality slippage more robustly.

Description: Explore insights to non-traditional actuarial roles from a panelist with experiences in data science, finance and entertainment. The panelist will be sharing their perspectives on their non-traditional actuarial role in relation to the actuarial profession.

Description: CMS has required hospitals to publish their chargemaster rates, cash discounts and negotiated rates as of January 1, 2021. Our panel is comprised of a data strategist, an executive from a large hospital system and an actuary.

Description: This webcast will walk through several statistical methods for imputing race and ethnicity from U.S. datasets, highlighting their strengths and weaknesses, talking about how to use them and evaluating their accuracy, and telling you where you can get code packages as well as a free dataset to try the methods out.