Description: At the end of this session attendees will understand how their company's existing cash flow models can be leveraged to meet the new requirements for principle-based reserves under VM-22.

Description: The upcoming VM-22 standard promises significant changes for the non-VA life insurance industry, impacting regulatory compliance, risk management, and financial reporting. This presentation equips insurance companies to navigate this crucial transition. We'll delve into key considerations from capital, modeling, and hedging perspectives, providing actionable insights for optimizing your VM-22 implementation strategy.

Description: The session begins with a brief introduction to Gen AI, including “what it is” and how to optimize outputs.Then, we will to provide some insight into what we are seeing within the Actuarial space – this would include the extent to which actuaries are using Gen AI on a day-to-day basis, how they are going about using it, and some predictions as to where this will go. Finally, we will dive into specific actuarial use cases – we have a few bespoke built actuarial demonstrations to show and will supplement this with a discussion on the broader spectrum of actuarial use cases. We plan for this to be the bulk of the session.

Description: Actuarial projects have become more intricate, involving external resources and requests beyond the Actuarial team’s purview. Whether a task appears minor or exceptionally complex, adept project and change management play a pivotal role in successful execution. In this session, we explore practical strategies for tailoring implementation management approaches. Our presenters draw from both corporate and consulting experiences, sharing valuable lessons. Additionally, they highlight effective collaboration with the Project Management Office, model developers, and model users

Description: This session will introduce attendees to a variety of powerful tools in Excel designed for manipulating and analyzing large datasets, including seriatim data with millions of rows. Alternatively, the attendee with learn equivalent strategies using R. Both approaches can validate each other.

Description: In this presentation, we will delve into the latest investment trends transforming the life insurance industry. We will start with a comprehensive overview of the key asset classes and strategic allocation approaches commonly adopted by insurers. Our session will then examine emerging market dynamics, with a particular focus on opportunities in private credit and securitized assets. We will also highlight the practical implementation of Buy and Maintain strategies, including a detailed cashflow-matching case study, to demonstrate how these approaches can enhance yield potential, minimize trading costs, and optimize capital efficiency in light of evolving regulatory requirements. Through this case study, audience will gain insight into portfolio construction and the critical considerations driving investment decisions within the industry.

Description: Session 7A: Integrated Analytics for GLP-1 Therapy Management: Optimizing Clinical and Financial Value

Description: How do social determinants of health (SDOH) affect health outcomes in the United States, how might SDOH factors be incorporated into financing and risk adjustment of Medicaid, and what implications might this have for market participants?

Description: Over the last 10 years, Artificial Intelligence (AI) healthcare foundation models have made tremendous strides when it comes to delivering highly accurate predictive results when compared to traditional models. This is especially true for models developed and trained on the ‘language’ of healthcare. When trained on healthcare data sequences (claims, EHR, CPT, ICD, pharmacy, lab, etc.), these models deliver far more accurate results as to WHAT beneficiary-level health events will occur and even WHEN they will occur.

Description: This session will discuss basic and advanced hedge modeling concepts. It will explain common hedge strategies used to support guarantees and options embedded within life and annuity products and the materiality of these products within the US. Attendees will learn how Machine Learning acts to reduce the computer processing needed to simulate the dynamic hedging of product liabilities projected in the future across many stochastic scenarios. Actuaries working in consulting, software development, and a large life insurance company will provide a wide range of hedging viewpoints ranging from a broad industry perspective to a hedging practitioner. Attendees will obtain a comprehensive understanding of a novel ML approach to modeling dynamic hedges and the hedge optimization opportunity it presents.