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: How does mortality experience impact earnings under the new GAAP financial framework? This article discusses how to isolate key components from financial models related to decrements, as well as how to handle the changes in the financial reporting landscape including: the aggregation of insurance policies into cohorts, dynamic reserving, and the limitations imposed by caps and floors. Looking at the components of earnings, such as the present value of benefits, expenses, and premiums, and how these elements interact is critical to form a comprehensive earnings story.

Description: We explore the question of how an actuary–artificial intelligence collaboration might look in the future and how actuaries should be trained to best leverage this technology. It felt fitting to accomplish this through a conversation with an AI system, as AI involvement is warranted to ground the analysis in the technology’s true capabilities.

Description: Expanding Horizons recently had the opportunity to interview Wenjun Zhu, the winner of the Society of Actuaries’ (SOA’s) third Actuarial Science Early Career Award.

Description: Actuary Dave Dillon describes his role volunteering his time as a teacher in higher education, including the rewards and challenges that teaching offers. He discusses the importance of being attentive to his audience’s pre-existing knowledge and adapting his presentations accordingly. His work as a teacher typically encompasses three distinct domains: 1) acquainting young students with the actuarial profession, 2) educating non-actuaries about public policy issues related to health insurance (including the Affordable Care Act), and 3) instructing current actuaries on advanced methodologies and principles within the field. Recently he taught a health insurance course for actuarial science graduate students at Georgia State University and lectured at Boise State University’s master's program in Population & Health Systems Management. In every teaching and mentoring opportunity, actuaries can contribute to the expansion and prosperity of the profession and are encouraged to pursue these endeavors.

Description: Private LTC insurers are paving the way for value-based care through working to implement care management programs that improve the lives of their policyholders before and during a claim. However, measuring the effectiveness of these new programs is a challenging task. In this article, we will explore powerful tools that can enhance traditional effectiveness studies and address some of their existing weaknesses.

Description: Al is reshaping the actuarial profession at an unprecedented pace. This article explores how emerging technologies—machine learning, generative AI, and automation—are transforming actuarial practice across pricing, reserving, and risk management. It highlights opportunities for actuaries to harness AI for deeper insights, enhanced predictive power, and more efficient workflows, while also addressing the challenges of transparency, bias, and ethical responsibility. The discussion situates AI within the broader context of professional standards and regulatory expectations, emphasizing the need for governance frameworks that safeguard trust and accountability. Drawing from real-world case studies and current research, the article examines how the actuary’s role is evolving from traditional modeling to strategic data leadership. It calls for continuous learning and interdisciplinary collaboration to ensure that actuaries remain central to the future of risk and finance. Ultimately, this article offers a balanced roadmap—one that recognizes AI as both a disruptive force and a catalyst for professional reinvention.

Description: Actuarial work in the life and health insurance industry is highly data-driven and complex. Actuaries perform a wide range of tasks such as experience studies, valuation, reserving, pricing, and risk modeling, all of which require vast amounts of data and sophisticated analytics. Traditionally, many of these tasks have been carried out using Excel and other legacy tools, but as data volumes grow and the need for more accurate predictions intensifies, actuaries are turning to more robust platforms. Cloud Data & Artificial Intelligence (AI) Platforms, such as t Databricks offer a unified platform that integrates data management, analytics, and machine learning, making it a powerful tool for actuaries. In this article, we’ll explore how Cloud Data & AI platforms can be used as an actuarial workbench, enabling actuaries in the life and health sector to streamline critical tasks like experience studies, valuation, and reserving.