Description: Artificial intelligence brings immense opportunities for productivity gains—and valid concerns. It can both support innovations in insurance products and in the customer experience as well as enhance our profession’s work. Actuaries share a responsibility for caution and professional judgment to use it without jeopardizing the fair and equitable treatment of individual consumers and the principals we serve.AI creates significant challenges for consumers: opacity, reliable accuracy, privacy, and verification of personal data. The Academy and its members have been working to educate and inform stakeholders, insurance commissioners, and regulators toward improving the transparency of algorithms that underlie the use of AI by insurers, to explain how the algorithms can be used to achieve equitable treatment, and to identify the issues and trade-offs related to ensuring consumer protections. We must amplify the actuarial perspective on how adequate disclosures, documentation, and governance of AI can help protect users. This session will examine how we can govern and support the evolution of better practices. We will discuss how AI is addressed via standards such as ASOP No. 56, Modeling, and other guardrails that are being developed to best utilize AI’s real-world potential and fulfill our professional responsibilities.

Description: At the conclusion of the session, attendees will be able to understand the potential for using global population health mortality and morbidity data in actuarial contexts. Using the Global Burden of Disease project as a resource, this session will discuss how novel population health research can be used to complement and fill in the gaps of existing input data sources for actuarial analysis and modeling. Presenters will share the latest academic research on the topics of demography, life expectancy, health-adjusted life expectancy, causes of death and disability, comprehensive disease incidence and prevalence metric, measures of disease burden for patients and populations, modifiable risk factors where there are opportunities to make interventions and improve health outcomes, and disparities between and within populations. This research is globally comprehensive and comparable between different markets and disease areas. The session will cover the motivation and purpose of GBD, a brief description of the models used, and dive deep on some selected use cases in actuarial contexts. Audiences will leave with: 1. Understanding challenges and opportunities in measuring disease burden comprehensively and consistently 2. Understanding relevant health metrics, including the drivers of future mortality and morbidity 3. Ideas for applications of epidemiological research in your work

Description: The expanded use of predictive models, algorithms and external consumer data has drawn the attention of the life insurance industry to the matter of fairness and bias in underwriting, including proposed regulation in states like Colorado and New York and a draft NAIC Model Bulletin. Insurers will benefit taking a proactive approach to verifying that their practices, both current and future, do not result in unfair discrimination. This session will help attendees in understanding potential requirements and reporting insurers must address, techniques and tools for evaluating bias, and challenges in doing so. At the conclusion of the session, attendees will be able to: o Understand proposed regulations and practices regarding fairness and bias o Identify tools and techniques for evaluating bias in their processes o Discuss the challenges the industry will face in addressing fairness in underwriting

Description: In this session, the panelists discuss several common cognitive biases that can adversely impact the capital allocation decision process, introducing the notions of time, accounting convention, positivity, hierarchy, and social proof in describing them. Historical case examples of sub-optimal capital allocation are then explored, identifying the contributing behavioral factors including the simultaneous confluence of multiple factors. The panelists will close the session with several suggestions for attendees to consider for incorporation into their decision-making processes. At the conclusion of the session, attendees will be able to: - Learn common cognitive biases that impact capital allocation decisions - Differentiate which biases impact different aspects of the capital allocation process - Build awareness of biases affecting capital allocation decision models - Mitigate cognitive biases present in decision making processes

Description: The session will start by looking at emerging trends in US population mortality improvement focusing especially on recent deviations from the traditional norms influenced by factors such as the prescription drug epidemic, aging populations, improvements in medical technology and socioeconomic differentiation. Explore the recently developed SOA Research Institute tool looking at US life insured mortality experience to see to what extent insights from the population view are present in insured mortality and how to make the best use of the tool. The session will conclude with observations on key points to keep in mind in your own understanding of mortality improvement development as well as engage the audience to gather your perspective.

Description: In this video, Chris Smith ASA MAAA, a health actuarial consultant and data science enthusiast, introduces the basics of machine learning and its applications in actuarial science. He covers various techniques, such as unsupervised, supervised, and reinforcement learning, as well as neural networks and gradient boosting. He also discusses the potential risks and ethical considerations of using these advanced technologies in the actuarial field. Contributors: Chris Smith, ASA, MAAA, Jason Reed, FSA, MAAA, Mitchell Momanyi FSA MAAA, Jessica Calafell, FSA, MAAA; Jon Forster ASA, MAAA

Description: As artificial intelligence reshapes the actuarial landscape, this panel will explore the critical aspects of change management necessary for the successful integration of AI technologies. We will discuss how to effectively embrace AI in the workplace and address common challenges and resistance to change. Join us for an engaging discussion on navigating this transformative journey and empowering actuaries to harness the full potential of AI in their work.

Description: Many companies are facing challenges with their inforce UL business. These “distressed” or non-core blocks of business can be a drag on earnings, return on capital, and/or internal resources. With the pressures of today's marketplace, companies are seeking efficient strategies for managing these blocks. The good news is that strategies exist such that inforce UL business can be optimized with some attention. Learn about some options and levers companies have available to help manage these blocks.

Description: This session will give an update on the latest in SOA Health Research. The session will also provide an overview of the health research process with additional information on upcoming SOA volunteer opportunities in Health Research. There will be a presentation on one or more SOA Health Research Projects recently published or soon to be published.

Description: In this video Dale Hall, Managing Director of Research at the Society of Actuaries Research Institutue, presents finding from a report on state-based catastrophic insurance coverage for long-term care in cases of conditions like dementia, ALS, and multiple sclerosis. Focusing on Minnesota as a representative state, the research explores stakeholder opinions on two program options: a comprehensive approach and a condition-specific model. While stakeholders favored a comprehensive structure, they highlighted operational challenges, the necessity of mandatory participation, and the importance of education and marketing efforts. The major takeaway is broad support for the concept, though overcoming operational hurdles and determining cost parameters are crucial for future program development. Contributors: Dale Hall FSA, MAAA, CFA, CERA , Rose Northon, STeven Siegel ASA MAAA, Jon Forster ASA MAAA