Description: Read the Quo Vadis Reinsurance.

Description: This article summarizes five key lessons we have learned in implementing LDTI and shares our insights on practical ways to address them. This is not an exhaustive list of implementation challenges, but companies that can successfully tackle the issues we describe should have a smoother data and systems implementation transition.

Description: This article highlights the findings of a recent SOA survey on accelerated underwriting (AU) practices, including the amount of AU business ceded, the results of three opinion questions, and an estimate of mortality slippage among AU programs.

Description: An application of GLM trees to mortality modeling using the Individual Life Experience Committee 2009-2015 dataset. GLM trees are a hybrid of GLMs and decision trees which are analogous to the way actuaries have analyzed data. The major benefits include speeding up actuarial analytic workflows, improving data understanding, and improving data visualization.

Description: Description and welcome to the 2020 Canadian Reinsurance Conference including highlight of the key note speaker

Description: Technology now supports customized non-level death benefits which help consumers optimize their coverage and cost. Creating individual policies and individually pricing them for a level premium quote is the start of personalizing and optimizing coverage and cost for consumers and pricing life insurance policies at the individual consumer level --- a revolution for actuaries.

Description: Part 2 of the article continues providing data on why IUL income streams need to be managed and suggests techniques that insurance companies could provide to policyholders and advisors to do so. The author also offers his research data free of charge to any actuary who contacts him to request it.

Description: Understanding the volatility associated with audit samples, as well as breaking out the different contributors to estimated mortality impact are vital tools in helping actuaries and underwriters make informed decisions about less invasive underwriting programs. This article walks through a sample example demonstrating how to calculate these metrics.

Description: S&P reissued a second Request for Comment (RFC) in May 2023 that proposed changes to their insurer capital adequacy methodology and assumptions, and suggested these proposed changes may become effective at the end of 2023. This paper is to highlight the notable changes between the current capital model criteria and the proposed model. We also discuss major changes from the first RFC and the second RFC, as well as several key items that still require enhanced guidance and clarification. Our analysis is based on information gathered from S&P's public comments, conversations with industry participants, and publications released by S&P Global as of July 2023 when this paper was written. Most U.S. life insurers are rated by S&P using their U.S. Life Statutory Capital model, while other insurers use the GAAP/IFRS Capital Model. Statutory financials will remain the starting point for U.S. life insurers under the proposed model, however there will be additional adjustments made to these numbers in an effort to create consistency and comparability with other accounting and solvency regimes.

Description: New digital data known as alternative data is everywhere. Our industry has seen the financial, and hi-tech industries leverage new digital data to expand their key offerings and core services. From the lens of the global life and health industry, new digital data is still searching to be further understood. Risk assessment is a current focus area for using alternative data. A key question is even though risk assessment has always been data-driven, can it now move to the next level with the arrival of this alternative data. Can we use alternative data to make the risk assessment process quicker, cheaper, or faster thereby driving more sales and better conversion rates. It is an exciting time! With the increased adoption of health and well-being apps, data such as physical activity, nutrition, sleep, and mental wellness is now readily available. Expanded data such as digital biomarkers, IoT data, electronic health records and many more can also be accessed. However, how to effectively implement alternative data remains a challenge across the industry. We firmly believe it is, and will continue to be, imperative to take a structured approach to alternative data through a set of key considerations and a framework of principles.