Description: Internal modernization initiatives and external changes of the financial reporting regulations (e.g., LDTI, IFRS 17) increase the amount of validation activities for actuarial models. In addition, the use of predictive analytics in actuarial modeling requires a different set of validation skillsets/techniques in model validation. These internal and external forces call for a structured, streamlined and robust model validation practice.

Description: The introduction and effective application of US GAAP LDTI have increased the scrutiny of those reviewing the updated financial results. That is because LDTI has resulted in significant changes in actuarial reserving and deferred acquisition cost (DAC) models for long-duration contracts, including significant changes to data, assumptions and required disclosures. In light of the changes, greater reliance has been put on companies’ model risk management (MRM) teams and model validations to assess the conceptual soundness and accuracy of their companies’ actuarial models and to assess that the underlying data and process utilized are suitable and appropriate. This article covers a brief background on model validation, walk through a sample LDTI-focused model validation framework/test plan, then provide insights on common LDTI-related validation observations based on the authors' prior validation experience.

Description: "Most patients enter the health care system through their primary care provider or through the Emergency Room or an Urgent Care Center. How an emergency room is structured, managed, and provides care is one of the major forces impacting the total cost of care. Yet it is often an after-thought and ignored by both health plans and health systems. In reality, the structured introduction of efficient practices can substantially reduce the quantity and cost of health care services. Further explore useful information to better understand and see how there are still substantial opportunities for improvement."

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: "Hear AM Best rating analysts discuss the rating process and the best capital adequacy ratio (BCAR), a quantitative foundation for AM Best’s assessment of carriers’ financial strength. The benchmarking of BCAR scores for various company types (national MCOs, BCBS plans, smaller regional plans) will be discussed. Look at how changes in investment and underwriting environment impacted the results over the past several years. Further, AM Best’s view of the quality of capital and various factors impacting the overall assessment of the balance sheet strength will be discussed. By attending this session, you will: Gain an understanding of AM Best’s building block approach to ratings and how the BCAR results fit into the process. Learn the differences between RBC and BCAR models. Learn how various factors—e.g. liquidity, financial flexibility, financial leverage, the org structure—impact the final AM Best assessment of health companies' capital."