Description: Come discuss the benefits and challenges of collaboration between academic institutions and industry stakeholders in shaping actuarial education and research agendas. Register for this event now.

Description: At the conclusion of this session attendees will be familiar with the status of the NAIC's GOES project and have a better understanding of the scenario sets under consideration and how they can be tested to assess the potential impact to principle-based reserve and capital levels.

Description: The post COVID-19 period exhibited a fast-changing capital market with higher interest rates, uncertain monetary policies, and revaluation of asset classes. At the same time, regulators introduced changes to reward better risk management, such as the scenario-based approach for reserving under Bermuda regulatory framework. For life reinsurers, while new opportunities arising from these changes, challenges also exist to be able to adjust reinsurance portfolios and ALM strategies appropriately. A holistic modeling framework can assist companies better position themselves in front of these challenges and other potential future unknowns. In particular, a well-designed stochastic and dynamic modeling framework enables the quantifications of such probabilities and potential impacts.

Description: "As digitization and automation rapidly progress in today’s life and health industry, issues with misrepresentation during the insurance application process are also becoming a growing concern for insurers around the globe. A recent survey finds that misrepresentation in application forms costs the average insurance customer an estimated 5% to 10% in higher premiums. In order to reduce this risk, insurers must find and correct areas of misrepresentation, consult post-issue sampling, review the automated underwriting processes, and monitor the quality of financial advisory firms. Learn how predictive disclosure modeling detects and reduces misrepresentation by harnessing readily available underwriting data to analyze issues, helping insurers understand various drivers for disclosure rates and areas of misrepresentation.Advantages of this modeling to various stakeholders in the life insurance journey include improved risk selection, claims experience, and reinsurance terms for insurers. For customers, it leads to increased certainty of coverage, payout of the claim, and ultimately lower premiums on average. By the end of the session, attendees will understand: The disclosure modeling process at a high level The technical details of a standard approach to disclosure modeling: data cleaning, standardization, visualization, and predictive modeling Success stories about how predictive disclosure modeling has impacted insurers"

Description: Virtual - Session 8D: An Application of Clustering Approaches in Value-Based Care

Description: "Can you answer the question 'what are the chances we will lose more than $1 million next year?' without saying 'it depends'? If you miss a projection, can you quantify the chances that the miss was due to random variation vs. an incorrect projection? ten in as presenters demonstrate how to answer these questions and others using total risk analysis. Total risk analysis includes quantifying both the random variation risk and the projection risk associated with actuarial functions like pricing and reserving. After attending this session, you will be able to describe total risk analysis, apply total risk analysis to many actuarial functions."

Description: In this presentation, actuaries and data scientists from Cleveland Clinic and Milliman discuss the development of a sepsis prediction model using machine learning. Presented with a unique challenge of handling massive amounts of data for near real-time risk scoring, the team took their model development to the cloud and delivered a product in less than a week through a unique virtual engagement.

Description: Explore the dynamic intersection of health insurance data and diverse industries beyond traditional health insurance providers. This session will delve into how life science companies, pharmaceutical manufacturers, device manufacturers, and others leverage health insurance data to drive innovation and decision-making.

Description: In this session, we will discuss best practices in ALM and Strategic Asset Allocation (SAA) modeling approaches to account for the complex relationships between insurance liabilities and the portfolios backing them. We will highlight how robust modeling techniques not only result in optimal asset decisions from a long-term value perspective but can also result in better capital efficiency. At the conclusion of this session, attendees will be able to identify the key aspects of a successful ALM and SAA framework for liabilities subject to PBR.

Description: A comprehensive webcast designed to bring together industry practitioners to discuss the current state of Model Risk Management (MRM) frameworks. This event will delve into the advancements in MRM, the challenges faced by professionals in the field, and emerging trends such as machine learning model validation that are set to shape the future of MRM. Engage with experts, share knowledge, and explore innovative solutions to enhance the effectiveness of your MRM framework.