Description: This article provides a brief overview of the current state of machine learning (ML) and artificial intelligence (AI) as they apply to actuarial science, including discussion around the integration of actuarial judgment with ML and AI. It concludes with an example of explainable ML through a python tool known as SHAP (SHapley Additive exPlanations), which is able to explain the key drivers behind individual ML or AI predictions.

Description: This chapter focuses on creating practical models that aid in the prediction of the risk of readmission to a specific hospital within 30 days of discharge for Medicare patients, to aid in the identification and stratification of at-risk patients for hospitals considering building an intervention program in a cost-effective manner. For readers who wish to develop their own predictive model, a dataset is provided on the Actexmadriver.com website, and R code is provided in the appendix to this chapter.

Description: The presentation provides an overview of the motor insurance pricing. It will highlight some good practices and important skills desired by the actuaries.

Description: This three-part series provides an overview of the rapidly evolving and dynamic gene and cellular therapy landscape, from the clinical, historical, and risk transfer perspectives. It covers the actuarial considerations in pricing cell and gene insurance and reinsurance, the value assessment of the therapies, manufacturer pricing, and reinsurance cost.

Description: Reunite with members and non-members in the China actuarial community to discuss recent topics and related issues in areas such as macroeconomic sharing, IFRS 17, product strategy, cross-border communication and discussion, and more. Advance your career through learning and networking opportunities, and share your experiences in the finance and insurance industries, as well as other fields related to actuarial science.

Description: This article is a brief overview of what digital health is, how it is regulated, and who some of the big unicorns are.

Description: Starting with a review of recent VA and FIA industry policyholder behavior experience, this session will explore several critical elements in developing a sustainable and coherent framework to translate this complex experience data to assumption models, particularly for guarantee features such as GLWBs. The discussion will include the use of industry- and company-level data in building customized predictive models, and integrating models across behaviors such as income utilization and surrenders.

Description: Reinsurance has been available for VA Guarantees for over 20 years. During that time, the reinsurance market for VA Guarantees has undergone frequent and sometimes violent transformations. Where does the market stand today? What forms and structures of reinsurance are available? Which VA Guarantee designs and features are easier to reinsure? Is reinsurance offered on both newly issued policies as well as in force/legacy books, and which vintages are difficult to reinsure? In an age of sophisticated hedging programs, what role does a reinsurer play in helping a VA writer manage this highly volatile risk? In this session, we will hear from a reinsurer that is actively writing new VA Guarantee reinsurance treaties in the U.S. and around the world, and from a VA writer that has successfully partnered with a reinsurer to enhance its VA product offering.

Description: With the rapid development of the Insurance market, insurance technology—including online insurance--continues to mature. Zhongan Online invests heavily in fintechand Zhongan Answer, an insurance robo-advisor, launched in 2018, could improve transaction efficiency by using artificial intelligence to communicate in a timely manner and solve the pain point of the perplexed insurance clause. Under a different consumption scenario, Zhongan Answer could reply to users in a timely manner, while also implementing private customized products and services by providing users with personal risk management and insurance assessment solutions so that users could easily and conveniently select the most suitable insurance plan. The intelligent shopping guide system of Zhongan Answer could improve transaction efficiency by analyzing the personal insurance intention and providing the humanized interpretation of insurance clause. Zhongan Answer has served millions of users and supported more than 100,000 insurance-related knowledge points with an accuracy rate over 90%. Zhongan Answer has provided more than four million Q&A services, and its intelligent shopping guide system covers more than 90% of insurance products.

Description: In the speech, the presenter will share her insights based on three aspects: 1. Investment management is an important part of the whole process of risk management; 2. Methods and processes of asset allocation as well as risk management considerations; 3. The interaction between liability and asset is critical to risk management.