Description: "Actuarial modernization is transforming the profession, and coding plays a central role. Coding skills enable actuaries to automate data manipulation, streamline model development and effectively harness advanced analytics. This session explores why coding is foundational to the future of actuarial work, highlighting practical use cases, essential technologies and career benefits. We will discuss the importance of coding and its return on investment for your career. The session will introduce several coding tools, demonstrating their practical applications to actuarial tasks, such as efficiently merging model changes. Attendees will learn key design patterns that enhance model maintainability and identify common anti-patterns that create errors and technical debt. Additionally, a practical demonstration will showcase how generative AI tools such as GitHub Copilot significantly boost productivity and simplify coding tasks for actuaries. Join us to discover how investing in coding - comparable in effort to passing one actuarial exam - can deliver lifelong professional advantages and position actuaries at the forefront of technology-driven innovation."

Description: You’ve written the position papers, updated the models, and designed the required disclosures, but you may be wondering how to explain the results during interim financial reporting periods to company management as well as other stakeholders. This session will explore ways to adapt existing management reporting and offer ideas for new metrics. We will explore various methods for analyzing DAC amortization patterns, market risk benefit reserve patterns, and Liability for Future Benefits (LFPB) movements. In addition, this session will explore ways to integrate changes in LDTI with business planning and other broader business issues such as product pricing considerations and reinsurance strategy.

Description: Cluster modeling is emerging as a powerful technique to manage cloud costs and run time. It also enables quick responses to "what if" scenarios, and aids in attributing results between reporting cycles. In this webcast, we provide insight into cluster modeling, present case studies that focus on various key performance indicators and discuss the benefits and challenges to cluster modeling from an insurer’s perspective. We also discuss the considerations associated with moving from an on-prem based computing solution to a cloud-based approach.

Description: Explore an overview of ChatGPT and Large Language Models (LLM) and the strengths and weaknesses of ChatGPT. We will discuss ramifications, including accuracy, privacy, copyright, bias, and intellectual property concerns, as well as potential use cases.

Description: Investigate the importance of collaboration with accounting, underwriting, sales, marketing and other professions as an actuary when you attend this webcast. Cross-functional positions can cause unique challenges to arise, like various experts attempting to balance growth and profitability. Discover an opportunity to learn about relevant ASOPs and dive deeper into contemporary examples that highlight specific professionalism issues that can develop.

Description: Modifiable risk factors stand out today as significant contributors to diseases, and yet we as an industry haven't tackled this. Instead, we sit by almost passively as obesity, diabetes and hypertension rates continue to skyrocket. In fact, obesity and overweight is now over 70% of the US population and has turned into the forgotten pandemic. Globally, no country in the world has improved their obesity percentage rates during the past 15 years. Insurers are starting to explore health interventions which have the potential to reduce claims and change people's behavior.

Description: Expect to learn how recent advances in AI and Generative text technology can help unlock data from medical records to solve many key underwriting and actuarial challenges. Specific topics include the following: - What is NLP/AI/machine learning and how is it currently being used in underwriting? - What technological advancements have Insure Techs made in the use of AI and GPT, and how are carriers/reinsurers utilizing these enhancements? - How can you avoid some of the challenges with GPT such as Hallucinations and 'black box' outputs? - How can extraction of data from medical records assist actuaries with various pricing and analysis challenges? - What legal/compliance challenges should users be aware of and how to manage those risks?

Description: Starting a company can be challenging, and growing a company is even more challenging. There is no simple template for success. The panel, who each founded their own companies, will discuss their experiences growing these businesses, including hiring, challenges working with large companies, managing IP, fundraising and marketing. Attendees will have the opportunity to ask questions and shape the conversation.

Description: New digital data known as alternative data is everywhere. Our industry has seen the financial, and hi-tech industries leverage new digital data to expand their key offerings and core services. From the lens of the global life and health industry, new digital data is still searching to be further understood. Risk assessment is a current focus area for using alternative data. A key question is even though risk assessment has always been data-driven, can it now move to the next level with the arrival of this alternative data. Can we use alternative data to make the risk assessment process quicker, cheaper, or faster thereby driving more sales and better conversion rates. It is an exciting time! With the increased adoption of health and well-being apps, data such as physical activity, nutrition, sleep, and mental wellness is now readily available. Expanded data such as digital biomarkers, IoT data, electronic health records and many more can also be accessed. However, how to effectively implement alternative data remains a challenge across the industry. We firmly believe it is, and will continue to be, imperative to take a structured approach to alternative data through a set of key considerations and a framework of principles.

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.