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 article identifies why insurance innovations take so much effort and digs deeper into the underlying causes. It shows and explains the importance of taking an efficient, tactical, and intentional approach when innovating to avoid over-building and over-investing.

Description: Mental health, suppoting policyholders

Description: In the wake of the pandemic, much of the insurance industry is now endeavoring to find sustainable, longer-term solutions among many forced innovations – and to ensure that temporary adaptations add value beyond mere change.

Description: A news release announcing the winners of the 2024 Student Research Case Study Challenge.

Description: Python has become the fastest-growing major programming language in the world. It has surged in popularity over the last decade, following the development of its industry-leading capabilities in data science, machine learning and artificial intelligence, and it is now one of the most globally popular and widely used languages. In this article, I discuss some of the reasons for its popularity and explain why many actuaries and insurers have started using Python.

Description: Discover more about key Economic Scenario Generation (ESG) topics that are relevant for actuarial applications. Expect a focus on risk-neutral / market-consistent ESGs, like setting long term assumptions and scenario reduction. Long tern assumptions will focus on a basic introduction to challenges in deriving long term assumptions and key concepts to better understand how those are set. Come explore a basic overview of scenario reduction techniques and challenges as well as common sense criteria to address the reasonableness of the reduction.

Description: Renal disease is a very heterogenous medical condition whose end state is dialysis, a recurring cost intensive medical condition. Dialysis cost is one of the major medical cost drivers in USA. Insufficient and improper care management in the early stages of CKD (chronic kidney disease) leads to early incidence of end stage renal disease (ESRD) among CKD patients which not only leads to high medical costs, but also reflects poor health quality.

Description: Regression to the mean is a phenomenon that arises when comparing sequential data points. It states that when an initial observation is extreme or an outlier, future observations will be closer to the average. Health care actuaries need to understand and be able to mitigate the effects of regression to the mean to avoid misapplying predictive models or misstating measurements of historical effects.

Description: Interview on opportunities for InsurTechs in Life and Health reinsurance. Themes covered include digital distribution and digital health data. The article also shares insights into the role of the reinsurer when working with InsurTechs.