Description: Businesses across the board have been drastically impacted by the effects of COVID-19 over the course of 2020, and insurance was not immune. Perhaps most relevant to this industry’s current capital and liquidity concern is the prevailing low interest rate environment. This has been a global trend in the last decade, and treasury rates in much of the developed world are at or near zero. Reduced investment returns limit an insurer’s ability to achieve their desired return on equity, eliminating previously profitable strategies that depended on the leverage of life and annuity balance sheets. Focus and activity have instead shifted to other methods to counteract the low interest rate markets and accompanying capital strain. Examples include increased mergers and acquisitions (M&A) activity within the insurance industry and an increasing focus by private equity firms in the insurance market for asset-intensive products, both of which reflect the goal of increasing yield rates on capital.

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.

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: This article provides an EV overview, current industry usage, key considerations illustrated by MetLife’s strategic spin-off of Brighthouse Financial, as well as implementation notes.

Description: Discount rate curve construction has been a topic of renewed interest following recent changes in financial reporting standards. Interpolation is a key component of curve construction and can be conducted via an assortment of methods. This article explores six popular interpolation techniques and assesses how they perform with regards to desirable features of such methods: continuity of forwards, stability and locality, simplicity, and market consistency.

Description: A Framework for Managing Surplus by David N. Becker from The Financial Reporter, May 1999, Issue No. 39.

Description: The article is based on a study of root causes in insurer insolvencies and impairments, with the focus on potential risk factors and prevention measures.

Description: This article examines potential approaches to the calculation of the risk adjustment component, with a focus on a case study related to a UL product.

Description: We explore the considerations regarding discount rates in the new US GAAP Targeted Improvements, including selection of observable rates and methods for extrapolations rates where there is no observable data.