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: This report presents an analysis of the NAIC climate risk disclosures for reporting year 2021. The 2021 disclosures were the most recently available data at the time this analysis was conducted (in June and July of 2023).

Description: IFRS 17 will be effective as of 1 Jan 2023 and provide opportunities as well as challenges to both Direct Writers and Reinsurers across the insurance industry. If the new framework is not fully understood, an implementation can elevate the risk of problems in financial reporting, product development, investment management and more. The transition to IFRS provides an opportunity for companies to optimize the financial position of the enterprise by implementing mitigating strategies to reduce the risks and challenges that IFRS brings to the table.

Description: In this article, we collected data from the companies’ roll-forward disclosures related to calendar years 2021 and 2022 on Market Risk Benefit and shared a high-level summary of the Market Risk Benefit volatility that a focus group of companies incurred and summarized the most common ways to mitigate volatility.

Description: The Taxing Times Editorial Board acknowledges the invaluable contributions of our colleague, Art Schneider, who passed away in August. Throughout his career as a tax accountant, Art generously shared his time and talents to help actuaries and other tax professionals increase their understanding of insurance industry tax topics. We will miss him.

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: Explore real-life experiences implementing LDTI for traditional life and annuity products. Learn about strategies that worked well and pitfalls to avoid in the future. Topics include data and assumption management, building disclosures for attribution analyses and roll-forwards, discount rates, implementing new DAC calculations, reinsurance accounting methods, and risk-neutral ESGs and processes to calculate Market Risk Benefits.

Description: If you're intrigued by the impact of recent interest changes or updates about the Principle Based Reserves ASOP 22 Statements of Actuarial Opinions Based on Asset Adequacy Analysis for Life Insurance, Annuity or Health Insurance Reserves and Other Liabilities, then this webcast discussion featuring three expert speakers will grab your attention. Join us for the annual Year-End U.S. Statutory Financial Reporting Considerations webcast and discover more about cash flow testing, as well as potential changes to statutory financial reporting due to climate change. This popular webcast will be taking place December 14, so don't miss out on the latest considerations from our important speakers.

Description: The annuity market has been declining while the Registered Index Linked Annuity (RILA) market has been expanding. Discover why the market is growing along with key features and considerations for the product from an actuarial perspective.

Description: ALM and hedging can reap significant benefits from innovation in computation and operations research. Explore applications of static and dynamic optimization in two different ALM and hedging use cases. Insurers are increasingly moving offshore by establishing Bermuda captive reinsurers. In calculating the Bermuda Best Estimate Liability ('BEL'), reinsurers will need to segment assets to support liabilities in each treaty. A Linear Programming ('LP') problem can be formulated to tactically select assets in a way that minimizes the BEL and consequently the total asset requirement. Learn more about what US Variable Annuity Insurers face with the regulatory requirement to reflect 'future hedging strategy' in their statutory funding calculation. The traditional numerical method of finding the optimal hedging target and then allocating assets may encounter the curse of dimensionality with expanding product and economic environment complexity. A Reinforcement Learning algorithm may well fit this problem and provide insurers a solution for dynamic hedging.