Description: Learn from panelists from different companies as they come together to discuss their experiences.

Description: Latest in our on-going series in which we have a candid discussion with one the insurance industry's most respected and high profile risk practitioners

Description: The speakers will discuss the replication of long-term options, including a discussion of issues such as liquidity, transaction costs, slippage, impact of policyholder behavior, and machine learning algorithms to improve hedge effectiveness.

Description: The speaker will discuss the training of neural networks to compute future Greeks of liabilities (or options) without the use of nested stochastics.

Description: Editor's note in Risk Management

Description: The article argues that effective Enterprise Risk Management (ERM) should be tailored to fit a company’s unique characteristics rather than forcing a standardized "best practice" approach. Drawing from decades of experience, the author explains that companies often reject rigid ERM frameworks that don’t align with their business culture, risk philosophy, or strategic priorities. Key challenges include resistance to aggregate risk tolerance, formal governance structures, emerging risk management, and capital models that expose underperforming business units. The article suggests four steps for aligning ERM to a company: clarifying ERM objectives, understanding risk culture, leveraging existing risk management strengths, and committing to an iterative improvement process. A well-aligned ERM program can enhance strategic decision-making and resilience by being embraced rather than resisted.

Description: Because of the short-term nature of most health insurance products, the sophistication of insurers’ capital modeling tends to lag that of longer tailed life insurers. Additionally, some health insurers treat required capital modeling as a compliance exercise. However, there is considerable value to insurers who take more thoughtful approaches to capital modeling and integrate their capital modeling outcomes into the strategic decision-making process. Gain an overview of common required capital measures, including the advantages and disadvantages of each, and see a demonstration on how some capital measures are deficient for strategic decision-making. In the second half of the session, you will examine a case study of the considerations, design, implementation, challenges and outcomes of integrating a complex economic capital model into the strategic decision-making process.

Description: Risk management techniques do not include system science. System science requires that the uncertainty of the world is incorporated into the results. The articles explains the difference between risk and uncertainty. Learn how risk practices create an overoptimistic view of future outcomes.

Description: Apart from their operating environment and the core risks they help others mitigate, organizations are largely impacted by behaviors--particularly those of their policyholders. This session builds on the first session in this series by considering how medical advances might influence policyholders, while also considering how agents/brokers, product design, and the economy can also be influencers. Weigh whether and to what extent behavioral uncertainties have been adequately integrated into the firms' assessments of business performance, both past and future. The presenters will also highlight activities being undertaken by firms to influence behaviors, in part building on the second session in this series by considering these activities through a regulatory lens. This session is for anyone interested in enhancing their understanding of uncertainty due to behavioral factors.