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: This article provides an alternative method to the computation of the Reduction in Benefits Test under 7702A. Part 1 provided for reduction in death benefits. Part 2 provides for reduction in Qualified Additional Benefits.

Description: Discusses insurance company considerations and approaches when dealing with the complexities of deferred lives within pension plans.

Description: This article will examine four approaches under two different methods (eight in total) used to combat the non-additivity of key rates and will compare them under a number of rate environments.

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: 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: This article updates the reader on the Doctoral Stipend process.