Description: This article is an interview of Stuart Klugman, senior staff fellow for Education at the SOA, who explains the changes to the pathway to earn the ASA designation.

Description: This article summarizes the second Simon Conference for young researchers in Actuarial Science, Risk Management, and Insurance, which took place at Michigan State University last November. The intent is to publicize the event and promote future participation in similar conferences of young researchers. The article will contribute to expanding the horizons of actuarial research performed by the academic community. Participation in the conference also gives professional development opportunity for practicing actuaries.

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: Climate risk modeling is taking center stage. With businesses increasingly expected to show how they assess, adapt to, and mitigate the risks of climate change, companies are asking: What is the right climate risk modeling approach for our business?

Description: The direct and indirect effects of the pandemic have impacted many actuaries’ work since the spring of 2020. This article addresses three considerations actuaries should account for when using risk evaluation models which are focused on projecting remote, highly unlikely losses: model effectiveness, asset risk, and insurance (mortality and mortality) risk.

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.

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: As actuaries, we’re trained to see patterns in numbers and to design solutions that mitigate risk. But I can tell you from experience that while quantitative analysis and modeling are critical actuarial tools, looking at the numbers alone can lead to insurance products that don’t succeed in the real world the way the math says they “should.” With new digital technologies, we have more data at our fingertips than ever before, but I believe it’s equally as important to bring qualitative research methodologies into your product development process if you want to design solutions that meet real needs in the market. In this article, Amanda Turcotte shares what happens when qualitative research is neglected or ignored, what happens when you incorporate it into the product design process, and how to implement qualitative research practices in your organization.

Description: This article delves into the transformative realm of Business Intelligence (BI) tools. We explore the fundamental functionality and structure of these tools, and through case studies illustrate how they offer valuable insights into carrier experience and underwriting dynamics. From real-time data visualization to in-depth data analysis, discover the essential features that empower businesses to make better informed decisions.

Description: This article discusses key considerations and differences in measurement requirements between IFRS 17 and LDTI, leveraging a term insurance example to illustrate potential impacts on liabilities and, ultimately, earnings emergence.