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: An introductory article describing how Bayesian statistics has evolved over the past 20 years and why it offers the actuarial discipline powerful tools to better understand and manage risk. Compared with traditional (frequentist) and black-box (machine learning) approaches, Bayesian analysis provides explainable models focused on distributions of estimates instad of simply point estimates.

Description: Gather with members and non-members in the China actuarial community to discuss recent topics and related issues in areas such as macroeconomic sharing, pension, investment, product strategy, and more.

Description: Come discuss how reinsurers can work side by side with insurer to better develop products, and lift in the areas that reinsurers have more experience, help matching products with distributions (or vice versa) and provide advanced technologies associated with tools and software. The speakers will also present Direct to Consumer plan from various points of view, i.e., distributors, carriers, and reinsurers. Some case studies will also be presented where traditional reinsurers and asset-intensive reinsurers helped insurers bring products to life.

Description: Strategic Risk Management was given lower priority in a recent survey of ERM Objectives. This article tells how the author believes that recent events have caused many to shift to a more short term focus and in the future there will be a shift back to a priority for the longer term view that stands behind Strategic Risk Management when the environment settles down and things again seem to be more predictable.

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: This is the second part of a 2 part series on Real options analysis (ROA). This article looks into the limitations of using financial option theory when doing real options analysis with projects that are long-dated and uncertain, such as: 1. First-degree homogeneity, 2. Uncertainty must derive from Brownian motion, and 3. Risk neutrality.