Description: Sometimes, rare things happen and the least expected occurs. Indeed, some events occur once or twice in a lifetime leaving little room to learn from experiences. In financial markets, extreme events, no matter how rare, could have a profound impact on a company or even the whole country. Insurers are also not free from the impact of catastrophic large-scale extreme events. As a result, with pervasive economic and financial revolutions sweeping our world and potential devastative catastrophes, the increasing interest in tail risk management is fuelled by practical issues, including investment downside risk and insurance catastrophe risk. Thus, developing statistical techniques to model extreme investment and insurance losses is certainly a major task for risk managers. the purpose of our paper is to apply moment methods to estimate the joint events such as concurrent extreme investment loss and insurance loss. A novel aspect of this article is that it takes into account the correlation between different assets and insurance lines of business.

Description: The direct and indirect effects of the pandemic have impacted many actuaries’ work since the spring of 2020. This article addresses three considerations actuaries should account for when using risk evaluation models which are focused on projecting remote, highly unlikely losses: model effectiveness, asset risk, and insurance (mortality and mortality) risk.

Description: This paper investigates techniques for the assessment of model error in the context of insurance risk analysis.

Description: Findings from EY Insurance Risk Management Team's 2016 (annual) Insurance Chief Risk Officer Survey.

Description: A presentation at the Actuarial Research Conference in August 2006 in Montreal. This paper discusses the Basel VaR Value at Risk test of a bank's VaR model. It proposes an alternative, Quality Control of Risk Measures QCRM Hypothesis test. The alternative is more likely to reject an incorrect VaR model.

Description: This paper investigates techniques for the assessment of model error in the context of insurance risk analysis.

Description: Explores the open vs. closed systems debate with regards to actuarial modeling and exposes the over-simplification. Valuable for anyone who uses models.

Description: As providers are considering accountable and value based care models, it is critical to strategically think through how to achieve a sustainable business model into the future. This requires actuarial and clinical/provider capabilities to assess the care management and financial levers to help a client through the transition.