Description: This article will evaluate two different novel techniques for approximating change in value of a portfolio due to the change in the interest rates that do not rely on the industrywide ALM metrics. These approaches use deterministic runs created to understand the range where ALM metrics could be relied on and one of these techniques could be more superior to the use of key rates for managing one’s portfolio when they are used in approximating value change for a change in interest rate.

Description: Strategic Risk Management was given lower priority in a recent survey of ERM Objectives. This article tells how the author believes that recent events have caused many to shift to a more short term focus and in the future there will be a shift back to a priority for the longer term view that stands behind Strategic Risk Management when the environment settles down and things again seem to be more predictable.

Description: An update on the activities of the JRMS Council.

Description: An update on the activities of the JRMS

Description: Discover the latest insights on emerging risks in the Indian market with our comprehensive survey report. Uncover key findings on financial volatility, disruptive technology, and climate change, and learn how AI is reshaping risk management. Compare these results with North American trends and explore the optimistic economic outlook for the India market in 2025.

Description: This report captures expert insights from a March 2025 roundtable on how generative AI is shaping actuarial work and insurance industry practices.

Description: Artificial intelligence (AI) presents numerous opportunities in the insurance and financial industries. It also comes with heightened model, operational, legal and compliance, financial, and data risk. In this session, we will discuss speculation that emerging AI capabilities have sparked the fourth industrial revolution, examine what is different about this most recent round of capabilities, and examine why industry experts warn about the heightened risks the use of AI presents. We will review a framework - which includes AI ethical principles, standards, and best practices - to govern the use of AI. This will include a cross-reference of relevant Actuarial Standards of Practice as well as industry guidance like the NAIC Model Bulletin on the Use of AI Systems by Insurers. This framework will help actuaries and insurance professionals gain confidence that - if governed appropriately - we can reap the vast rewards of using AI systems in our industry.

Description: Behavioral Science is a powerful tool to enhance customer experience and improve outcomes across the life insurance value chain. This session will cover the foundations of behavioral concepts in a life insurance context and discuss practical areas that can benefit from behavioral science including customer engagement, disclosure, and retention. The session will leverage recent SOA research and specific experience in communication campaigns and call center best practices to translate theory to quantified results. Attendees will leave with an appreciation for potential challenges and practical steps to measure and demonstrate the value of implementing behavioral science.

Description: To provide high level information on a book selected and discussed during the December book club session, The Ten Commandments of Risk Leadership. In addition, this article serves as a promotion of the SOA book club as well as the upcoming sessions.

Description: We explore four plausible scenarios for how AI might reshape the future, focusing on employment as the main driver. At one extreme, AI boosts productivity, sparks entrepreneurship, and leads to near-full employment through human-AI collaboration and reformed education. At the other end of the spectrum AI-induced mass layoffs trigger an economic spiral, with soaring unemployment, creative stagnation, and societal resentment. The middle path presents a fragmented transition with a two-tier workforce, periodic recessions, and variable adaptation success. Lastly AI fizzles due to poor returns and rising costs, causing economic stagnation and investor losses without widespread disruption. Each scenario also includes potential impacts on the insurance industry, ranging from innovation and growth to regulatory strain and investment losses in the others. Proactive scenario planning, by preparing for multiple futures by identifying early warning signals, adapting plans, and strengthening institutional resilience is encouraged. The article closes with four additional speculative scenarios, including government-controlled AI, AI dominance, militarized AI, and mass surveillance. Ultimately, the piece argues that while AI’s future is uncertain, the choices made today will shape whether it becomes a partner, a threat, or a disappointment.