Description: The insurance industry is working rapidly to understand the potential for transformation as artificial intelligence reshapes how products are marketed and distributed. This webcast brings together founders and senior leaders at the forefront of this change to discuss how AI is being applied to better understand customer behavior, personalize outreach, streamline lead generation, and improve distribution efficiency. Discussion will focus on future use cases and how the use of AI in marketing could change product design and customer behavior.

Description: This session will explore the considerations and best practices for developing AI tools that are useful, safe, and transparent for actuarial work. While large language models (LLMs) offer exciting possibilities, it is crucial to understand when and how to use them effectively. The session will cover key concepts of LLMs and case studies on developing AI tools for retrieval-augmented generation and summary creation of actuarial documents. Attendees will learn about the importance of designing workflows that nudge users towards safe and effective processes. By the end of the session, participants will gain insights into the responsible use of LLMs in actuarial practice and learn how to leverage their potential to support professional growth.

Description: Every year an AI topic goes through a hype cycle. Since 2022 and now in 2023 we continue to hear more about the ChatGPT models and how an everyday person is able to interact with AI. As more startups and applications are riding the hype, what does it all mean for our industry? Is this just a buzz or real? This talk intends to cover at a high level what are large language models, what does it mean for audit or regulatory space, and what might be some pitfalls or tolerance of error when it comes to selecting a right application for such models in insurance use cases.

Description: Insurers are now in a better position than ever to both understand and enhance their customers' health and well-being. A key avenue for this is through developing health and wellness offerings for clients—for mutual benefit. Around the world, the proliferation of lifestyle and health data continues to gather pace.

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: 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.