Description: The article introduces a cashflow matching strategic asset allocation (SAA) framework for life insurers. Given the recent shift to higher interest rates after two decades of persistent low interest rates, insurers have an opportunity to enhance their asset liability management by rebalancing asset portfolios to narrow duration gaps and attain higher risk-adjusted yields. The framework aims to align investment objectives with economic, regulatory, and rating agency requirements. It prioritizes cashflow matching as the primary optimization goal and incorporates security-level asset information to assist portfolio managers in executing SAA seamlessly. The article highlights the benefits of the cashflow matching SAA framework, including greater attention to cashflow matching, unbiased results, readily executable strategies, and stable economic reserves. A case study is included to demonstrate the effectiveness of the framework in improving risk-adjusted return and cashflow matching for a representative liability block.

Description: There will be inflection points in the value of an instrument when interest rates change. These inflection points could materially impact the approximation of value change using ALM metrics. In this part of the seven-part series, I will highlight: • How to identify the inflection points; • the range of rate changes where ALM metrics may be relied upon i.e., the “validity” range, outside of which recalculation of the ALM metrics is required and the potential that one needs to rebalance the portfolio; • a technique to improve on the approximation of value change beyond the validity range; and • a technique to convert non-linear change on the yield curve to be used with duration and convexity.

Description: A contract owner selects a payout for his annuity using an AI/bot. The AI/bot presents various options with differences in payment and interacts with him in a simulated chat session. He decides on the form of payout. Compared to regular customer service the AI/bot was an improved experience with a call to action for the industry to build it.

Description: A paper demonstrating how to obviate the need for market timing strategies in variable annuity products by judicious use of product design. The paper presents the premise behind the product design, provides numerical examples, then explores possible extensions of the concept to produce more sophisticated variable annuity plans based on guarantees of investment outcomes.

Description: Article reviews the data a year into the unwinding of continuous coverage provisions in Medicaid, the impact on enrollment counts, how capitation rates have been adjusted, and compares those results to what has been modeled with the SOA Mediciad Unwinding model.

Description: The Introduction to Modeling: Summer Boot Camp series provides an overview of modeling topics and techniques aimed at the beginner modeler. This interactive series is comprised of five 90-minute sessions with opportunities to discuss the topics in small break-out groups.

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: A news release announcing the winners of the 2024 Student Research Case Study Challenge.

Description: Presents a step-by-step methodology for calculating confidence intervals for IBNR estimates derived using the Averaqe PMPM method. It is a companion article to the January 2023 Health Watch article presenting the Average PMPM method for generating point estimates of IBNR with zero claims runout.

Description: Cluster modeling is emerging as a powerful technique to manage cloud costs and run time. It also enables quick responses to "what if" scenarios, and aids in attributing results between reporting cycles. In this webcast, we provide insight into cluster modeling, present case studies that focus on various key performance indicators and discuss the benefits and challenges to cluster modeling from an insurer’s perspective. We also discuss the considerations associated with moving from an on-prem based computing solution to a cloud-based approach.