Description: This article helps companies better understand the currently proposed upcoming VM-22 regulation by comparing the VM-22 measurement model to LDTI MRBs. The article highlights key considerations as companies plan for adoption of these two measurement models. These considerations should help inform a company’s strategy related to the business impacted by these standards.

Description: S&P Global released its initial version of proposed changes regarding its Insurer Risk-Based Capital Adequacy methodology and assumptions on Dec. 6th, 2021. Unlike prior guidance notes or criteria releases, the proposed changes comprehensively updated the current S&P rating criteria released in 2010. These updates would directly impact many insurers. S&P Global anticipates that 10 percent of existing ratings in the insurance sector would be impacted and the change would lead to more positive rating implications than negative impact. This article focuses on the proposed changes on the S&P risk-based capital (RBC) vs. the current model, then simulate impacts to a representative U.S. life insurer through an illustrative case study.

Description: Mandatory implementation of life principle-based reserves (PBR) is just around the corner, and there is no shortage of work to do, as most products have yet to be moved to PBR. Oliver Wyman recently completed its 2019 PBR survey, with more than 40 participants covering 85 percent of the individual life market, including 23 of the top 25 life writers and five reinsurers. This article will expand on the key survey findings including implementation status and model simplifications.

Description: This article provides a summary of the research paper and Excel-based tool that can be found on the SOA’s website at Regulatory Capital Adequacy for Life Insurance Companies: A Comparison of Four Jurisdictions | SOA.

Description: This article provides an overview of activities that should be considered by an actuary when validating a predictive model. It describes several components to consider when validating a predictive model and provides an examination of various methodologies that can be implemented in the validation process.

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.