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: 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: Risk adjustment is needed under IFRS 17 to reflect the compensation that a company requires for bearing the uncertainty about the amount and timing of the cash flows that arises from non-financial risk. Companies are also required to disclose the method and confidence level used for the calculation of the RA. However, IFRS 17 doesn’t specify a method and a confidence level, nor does it provide a list of specific risks that are considered to be non-financial risk. Companies need to define them based on their own preferences or existing practices. This article will introduce available approaches and discuss the confidence level approach with potential consideration stemming from industry preferences and illustrative examples.

Description: This article highlights the fact that new requirements for disclosure of average liability duration and interest rates could lead to diversity in practice. It also recognizes that elements of the new disclosure requirements will enable financial statement users to perform their own crude estimates of these averages in ways that could help them to better understand the liabilities and to compare companies using consistent methods. Finally, the article describes how companies might also find value in such crude estimates.

Description: The implementation of the IFRS 17 insurance accounting standard has brought significant changes to the financial reporting landscape of insurance companies. With new disclosure requirements and altered profit analysis, understanding and interpreting future profitability have become a topic of concern for the industry. While stability remains a key objective for insurance companies, the earning patterns might become more volatile especially when the contractual service margin (CSM) is exhausted, and a loss component (LC) needs to be established. Reinsurance, a common risk mitigation tool, can play a pivotal role in managing earnings volatility and minimizing losses for onerous measurement units. In this article, we propose a new key performance indicator (KPI) called “loss recoverability” to assess the performance of reinsurance treaties in achieving these objectives. We explain how this KPI can be utilized in multiple scenarios to evaluate the effectiveness of reinsurance strategies and pursue stability in earning patterns.