Description: This report explores AI bias in insurance and health data, highlighting the ethical role of actuaries and offering cross-disciplinary guidance for fairer decision-making systems.

Description: ACA risk adjustment has now been in play for years. The original intent of risk adjustment was to help stabilize the market through measuring risk levels of each issuer. However, the risk adjustment program may have introduced additional uncertainty due to annual market shifts and model changes, making risk adjustment estimation is a difficult task. This article analyzes the results over time, including impacts from market changes and model changes.

Description: Regulatory change and increased focus on internal risk management are driving a renewed interest in model efficiency. In this session, we will review several new and existing tools, that show significant promise for advanced modeling of equity linked products. These include: • Clustering • Use of unique--and potentially a different number of--scenarios for each policy • Semi Monte Carlo (SMC) – this is a proprietary technique that is similar to a combination of Monte Carlo and numeric integration • Using a neural network approach to optimize some of the more complex and manual aspects of clustering and improve the fit of the clustered model • Combining SMC with the use of unique scenarios per policy

Description: Retirees will face the societal issue of inadequate savings with likely insufficient time to rectify the situation. They need immediate growth, but also the disciplines of risk management. They typically do not know how to engage with these two aspects in a harmonious manner on their own. Insurance companies are in the business of providing the solution but regulators have been clamping down in favor of simpler and more transparent products. In addition, the market reality over the last decade has been that insurers have stock betas at a multiple to the general markets with PE ratios well below. A panel of senior professionals from writers of retirement product business will present their vision of how the insurance industry can address the above dilemma, including the risks underlying the writing of the business, impact of financial markets, and regulations in the development of the business.

Description: The implementation and execution of IFRS17 requires the insurance industry to re-define the skill set matrix of Actuary, Accountant and IT practitioner. Professionals with the ability to, 1. understand the business context of IFRS17, 2. gain insight from complex actuarial & accounting & data system 3. communicate technical content in a compelling way, will be the key players of the future Finance function of the insurance industry. They will also become the foundation of the new formations of IFRS17 delivery team containing hybrid or cross functional capabilities. This presentation will discuss: 1. the new skills, ranging from account posting to data governing, required by actuaries to stay relevant in a digitalized Finance function under the IFRS17 world 2. the actuarial related roles available within an E2E IFRS17 reporting process 3. the potential formation of the IFRS17 reporting team

Description: This chapter introduces a few probability distributions that play an important role in understanding and analyzing healthcare data. While theoretical in nature, these distributions model real life if appropriately chosen. Probability distributions are mathematical representations of how statistical data behave.

Description: There will be no easy resolution to the current trade friction between the U.S. and China. If anything, the motivations for increasing protectionism are set to intensify. What are these motivations? Where is this trade war headed? And what impact could this have on economies and financial markets?

Description: Describes several regulatory changes that may impact the actuary working in a small company. These changes are not related to Principle Based Reserving.

Description: Spark offers a way to get some dramatic speed and scalability advantages over the Map-reduce methodology whenever you are doing iterative data processing and particularly when you want interactive data analysis capability. Find out why “lazy execution” can be a desirable characteristic when dealing with big data.

Description: In the evolving realm of healthcare actuarial practice, value-based contracts are reshaping the landscape. This article explores the pivotal role of AI-enhanced Electronic Medical Records (EMRs) in empowering actuaries to navigate this dynamic sector. Despite challenges in data standardization, AI-enhanced EMRs offer a solution by extracting and standardizing diverse medical records. The article delineates how AI-EMR integration benefits actuaries and provider organizations, enabling more accurate forecasting, earlier shared savings prepayments, and real-time quality metric aggregation. Moreover, it discusses how this fusion addresses historical data limitations, can help project catastrophic claims, and can help identify risk score capture opportunities. Ultimately, it indicates the transformative potential of AI-EMR synergy, positioning actuaries at the forefront of healthcare analytics with unprecedented precision and insight.