Description: In the United States, there has been much industry discussion of the challenges associated with a sustained low interest rate environment, which impacts both the asset and liability sides of the balance sheet in unfavorable ways. The intent of this article is not to focus on these strategic issues. Rather, we attempt to shine a spotlight on some of the modeling challenges that practicing actuaries may experience when incorporating negative interest rates into their models.

Description: Provides an update, as of September 2022, on Financial Reporting Section sponsored research projects in process and those recently completed.

Description: Column from the chairperson of the SOA's Financial Reporting Section describing the research and webcasts available to section members.

Description: Welcome to the May edition of The Financial Reporter! In her “Chairperson's Corner”, Joy Zhang highlights the section's upcoming activities for the year and ways for everyone to get engaged.

Description: Pandemic impact on continuing education. Financial Reporting Section and Community Engagement. US GAAP textbook update for LDTI. IFRI textbook update for amendments.

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 description and status update on all recent research reports sponsored by the Financial Reporting Section.

Description: GAAP's elimination of gross profit as a basis for amortization of deferred acquisition costs enables the accounting for reinsurance of universal life contracts to better reflect the economic protection provided by reinsurance. It also makes it easier to assess the effectiveness of different techniques. Building on the analysis of an earlier article, "A Fresh Look at Accounting for Reinsurance of Universal Life," this article presents a practical approach to estimating the ineffectiveness of several existing techniques at accounting for the economic protection provided by reinsurance. The article ends with a summary of what a company might do to improve the effectiveness of its reinsurance accounting.

Description: Accounting Standards Update No. 2018-12, Financial Services – Insurance (Topic 944): Targeted Improvements to the Accounting for Long-Duration Contracts (LDTI) has been effective for most large, public business entities since 2023 and will be effective for other insurers in 2025. While the guidance clarifies the need for incorporating claim liabilities and premium accrual balances in the liability for future policy benefits (LFPB) under LDTI, companies may still have questions given there are limited details available around the techniques used in practice. In this article, we demonstrate the need for incorporating claim liabilities and premium accrual balances in the LFPB under LDTI. We also look at two potential approaches of incorporating these accrual balances.

Description: In recent years, vast amount of data from emerging experiences has helped insurers gain a deeper understanding of their policyholders and the factors driving their behaviors. However, due to limitations in traditional experience study methods, this understanding typically remains at the cohort level. This series of articles proposes a novel machine learning-based model that analyzes and predicts policyholder behaviors at the individual policy level. Policyholder embedding representations are learned using a Recurrent Neural Network (RNN) that takes into account the sequence of historical transactions associated with a policy. Additionally, a Neural Network with a multi-head architecture is trained to predict the policyholder's next action based on the policyholder embedding and other policy attributes. The resulting model offers several advantages over traditional experience studies and assumption-setting methods, including the ability to set policy-level assumptions that improve reserve accuracy, predict multiple behaviors simultaneously while capturing the interrelationships between them, and generate policyholder embedding representations that are useful for segmentation.