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: Pandemics are a main driver of losses for both life and non-life (re-)insurance. Until COVID-19, risk assessment mostly relied on a few historic examples, most importantly the Spanish flu. The COVID-19 pandemic has shown that other pathogens (namely the coronaviruses) need to be taken into account. Also, modern societies and governments drastically respond to novel threats and implement measures such as social distancing, mask mandates, and lockdowns. Besides the properties of the pathogen itself, these reactions and the medical progression (namely the development of vaccines) are key influences on the course of a pandemic, and thus also the resulting outcomes. To account for the new insights, join us as we take a look at a stochastic, age-structured compartmental model that is calibrated on recent pandemics with several parameters sets to model different levels of reaction speed and stringency between groups of countries. Other important factors also must be defined in close collaboration with experts. Get ready to explore the development of a model and framework that can provide potential outcomes to be used as the basis to derive both summary and tail statistics to assess pandemic risk and help price complex deals.

Description: Artificial Intelligence (AI) has become a key component of the insurance landscape and getting full value from an AI depends on much more than simply building the model. Please join us to hear the challenges and potential solutions around successfully deploying an AI-driven initiative within an organization. Hear from panelists as they describe the human impacts of model implementation, how to assess a model for effectiveness and (lack of) bias, and detail the journey of implementing AI-driven underwriting models at a large insurance company.

Description: Further explore the pipeline of large claims approaching in the future in this webcast. Some of these upcoming claims include Cell and Gene Therapies, as well as high medical costs. In order to prepare for the multitude of claims, this session provides the insurance industry with an overview of what these large claims consist of. You can also expect important recommendations on how to properly prepare for them to succeed in this market.

Description: Dive into an overview of potential customer value propositions, trends in consumer acceptance and adoption, solving the data portability issue, potential impacts of emerging partner ships with OEMs and more within the auto insurance industry during our latest webcast. Experience interactive dialogue that will allow another dimension of thinking as industry experts provide insights and expertise. Throughout this webcast, you can expect developments in the personal lines automotive telematics-based insurance landscape that will develop a further understanding of the present and future of this industry.

Description: Discover the impact of COVID-19 on member costs post diagnosis and the future of mortality in this Emerging Long Term COVID-19 Trends webcast. This webcast will be split up into Health and Life portions. During the Health portion of this webcasts, you will learn more about the impact on risk scores due to recent findings. Enjoy this discussion and further dive into the emerging COVID-19 trends that may affect how you conduct business practices. At the Life portion, the SOA Research Institute assembled a panel of mortality experts who will express opinions on the effects of the U.S. mortality rate for general, insured and pension populations in the short-term.

Description: ALM and hedging can reap significant benefits from innovation in computation and operations research. Explore applications of static and dynamic optimization in two different ALM and hedging use cases. Insurers are increasingly moving offshore by establishing Bermuda captive reinsurers. In calculating the Bermuda Best Estimate Liability ('BEL'), reinsurers will need to segment assets to support liabilities in each treaty. A Linear Programming ('LP') problem can be formulated to tactically select assets in a way that minimizes the BEL and consequently the total asset requirement. Learn more about what US Variable Annuity Insurers face with the regulatory requirement to reflect 'future hedging strategy' in their statutory funding calculation. The traditional numerical method of finding the optimal hedging target and then allocating assets may encounter the curse of dimensionality with expanding product and economic environment complexity. A Reinforcement Learning algorithm may well fit this problem and provide insurers a solution for dynamic hedging.

Description: The industry sees extreme value in predictive modeling and its ability to help us meet customer demands and remain profitable, but do customers and regulators look at this as a favorable addition to our process? Hear from a dynamic panel of industry experts who will tackle a variety of issues and questions from the state of the regulatory environment to the responsibilities of the carrier.

Description: Explore insights to non-traditional actuarial roles from a panelist with experiences in data science, finance and entertainment. The panelist will be sharing their perspectives on their non-traditional actuarial role in relation to the actuarial profession.

Description: Explore insights to non-traditional actuarial roles from a panelist with experiences in data science, finance and entertainment. The panelist will be sharing their perspectives on their non-traditional actuarial role in relation to the actuarial profession.