Description: Enterprise Risk Management (ERM) provides practitioners all of the tools necessary for assessing, quantifying, and managing risk on an aggregated, holistic basis. However, in practice it is often found that there is a tendency for company managements and even seasoned risk practitioners at times to navigate their risk exposures one at a time. This habitual approach produces sub-optimal results due to the oversimplification of risk events and understating the complexity of the world in which decision makers must navigate. At the heart of this sub-optimal behavior is the human predilection towards mental accounting. As with financial accounting, mental accounting employs a ledger function that mentally registers debts and balances. However, unlike a traditional ledger, the mental ledger is not precise, does not always sum debits to equal credits, and creates arbitrary categories for resources that are treated as independent, unrelated pools. These differences in function profoundly impact financial judgments and decision-making. Learn more about the long history of mental accounting, including examples from daily life to illustrate the principles involved. Discuss how mental accounting can arise during the ERM process cycle, with a special emphasis on its impacts on effectively quantifying risk and how this results in sub-optimal decision making. Discover behavioral tools specifically designed to mitigate the risk of mental accounting creeping into a company's ERM activities.

Description: In summer 2021, the SOA Research Institute’s Mortality and Longevity Strategic Research Program sponsored a webcast examining individual life and group life emerging mortality in a COVID-19 world. Since then, Delta and Omicron coronavirus variants have fueled waves of the virus in the U.S., boosting the total number of COVID-19 deaths since the beginning of the pandemic to near the 1 million mark. Hear an update and insights into how the life insured population is faring during COVID-19 by discussing the findings from two recent SOA Research Institute initiatives. LIMRA, Reinsurance Group of America (RGA), the Society of Actuaries (SOA) and TAI have collaborated to analyze the impact of COVID-19 on the individual life insurance industry’s mortality experience. Additionally, the SOA Research Institute has surveyed insurers to gather a high-level view of U.S. Group Term Life Insurance mortality results during the COVID-19 pandemic, comparing them to pre-pandemic mortality levels. The Group Term Life industry mortality results will be presented with monthly data through March 2022.

Description: Models are meant to represent reality, and they often do so quite well. However, they cannot make decisions that contradict the modeling algorithm or underlying assumptions and data. Neither do they possess emotional intelligence or the ability to adjust for social equality. As complexity of models evolved to predictive analytics and machine learning, reliance on model results has increased as well. Over the last decade, as actuaries, modelers and data scientists looked closer into their models, they often identified certain social biases in model assumptions and algorithms. From the use of indicators like credit scores to geo-social segmentation, insurance models have often skewed results in favor of certain socio-economic groups. Underlying this segmentation, one can identify bias around access to health care and education, socioeconomic groupings and financial literacy.

Description: Increasingly, actuaries need to collaborate and partner with clinicians in order to be successful in value-based care and population health initiatives. Gaining credibility with professionals from different backgrounds, training and sometimes different objectives can be a challenge. Gain perspectives from actuaries and clinicians to discuss how to collaborate and achieve stronger results and outcomes. By attending this session, you will be able to: • Identify common scenarios where actuaries and clinicians need to collaborate. • Understand perspectives on how to partner and communicate with clinicians. • Describe successful strategies that take into account improvement of financial and clinical outcomes. • Understand how actuaries can provide valuable data to drive results and demonstrate outcomes.

Description: Predictive analytics projects in the life insurance industry are oftentimes set up as research ideas leading to intangible or unusable results for the practicing actuary. What if you could change that? What if the research turned into development and practical use through leveraging valuable resources properly? Learn how to structure predictive analytics projects, and about the project team, so there will be actionable takeaways for the business unit. Specific areas of value for you include underwriting, experience studies, assumption-setting, and product development. Watch as presenters talk through real case studies on turning a predictive analytics project into workable solutions rather than a resource drain, an unclear goal, or a misunderstood business need, which are some of the pitfalls of a poorly planned project.

Description: The old adage 'insurance is sold not bought' has been used to dismiss digital insurance and support the old agent model of distribution. However, modern distribution systems address this with personalization. This is not simply a customized application form based on age or gender. Personalization is much more dynamic and happens in real-time. It's about tailoring the end-to-end experience to meet the needs and expectations of the specific applicant. The core tools to achieve this are AI learning and nudges from behavioral science.

Description: Come discuss inforce management techniques that go beyond the traditional methods of adjusting non-guaranteed elements within contractual limits. Methods such as retention, cross-selling/up-selling, wellness, exchange programs and other customer behavior initiatives will be presented with relevant considerations.

Description: Over the last several years, the life and annuity industry has seen significant reforms to the Valuation Manual and RBC Instructions, but one outstanding item not yet addressed with recent 'VA Reform' was the economic scenario generator (ESG). The NAIC has engaged Conning, Inc. to replace the Academy's generator (AIRG) that is currently benchmarked for VM-20 and VM-21 calculations. Learn about a broad overview of the current statutory ESG reform, and possible considerations companies need to account for in the reserve and capital calculations dependent upon it. You'll explore a brief regulatory history of the ESG efforts, as well as key mechanical differences between the proposed Conning 'GEMS' model and the AIRG. We will also examine key statistical differences between the model outputs, potential implications for company risk management, and pending regulatory changes to consider before official implementation of the new ESG. With industry field testing recently completed, review of this new scenario set is still ongoing. This initiative is extremely important to the industry because it could ultimately have significant implications on companies' regulatory requirements and risk management strategies.

Description: Many insurance companies have started Diversity, Equity, and Inclusion (DEI) initiatives over the past few years to better engage with their employees and communities in new ways. Explore another important audience of DEI programs: the customers who purchase insurance products. Review research on the unique needs of specific groups that may have been underserved by insurance companies in the past. You will also touch on ways to make the insurance buying process more accessible to everyone.

Description: Agility, responsiveness, and real-time access to data are critical today, and they become even more critical tomorrow. As business leaders, we need to drive a more responsive decision-making culture, and we can do this by utilizing the concept of continuous improvement. Discover how an agile company can increase its financial IQ to improve the speed, openness, confidence, and frequency of finance-led decision-making - and ultimately position finance as the strategic core of the organization.