Description: Credibility is a mechanism for estimating a quantity of interest by combining subject experience and relevant experience to improve the estimate.

Description: Attend if you are an organization interested in utilizing various kinds of client data to improve the whole insurance sales process, and to develop new applications. Interested parties may include distribution sales force, underwriting, claims, actuarial and finance departments within a typical insurance company, online distribution partners, health care providers and other consulting service providers. The research looks into various use cases, which are typically main issues in modeling in the insurance industry. The research also helps benchmark performance using different languages that may serve as a good reference when best to use a certain language to enhance the development cycle.

Description: Cover a variety of topics centered around the unsupervised learning technique called 'clustering'. The presenters will take you through a wide array of topics that range from 'What is Clustering?' to 'How can I use this technique to solve problems I didn't even know existed?' In the health care industry, everyone is looking for an edge in reducing total spend-cluster analysis finds the unambiguous in an ambiguous framework of results.

Description: At the conclusion of this session, attendees will be equipped to apply relative risk curves in their actuarial work, including the ability to examine dose-response relationships, apply population attributable fractions (PAFs), and develop customized risk models for cause-specific mortality and morbidity outcomes based on individual-level exposures to selected risk factors. These skills are becoming increasingly important as actuaries adopt novel applications of big data and dynamic health information to refine risk assessments and keep pace with global health trends.

Description: This report introduces quantum computing to actuaries. In addition, this research will assess and identify areas in the insurance field where quantum computing can make a difference, accompanied with suggested algorithms.

Description: This paper introduces practitioners to the selection and calibration of stochastic interest rate models. Six continuous time interest rate models and their calibration are presented. Actual code and data examples are added to help the practitioner implement them. The emphasis is on hands-on calibration with RStudio. The reader is assumed to have a working knowledge of RStudio, including writing R scripts.

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: An overview of the objectives of outbreak modeling, and an examination of the various types of models used both to forecast an uncontrolled outbreak, and to estimate the effects of interventions intended to alter the outbreak’s trajectory

Description: Similar to how states had made adjustments to their capitation rates to reflect acuity adjustments caused by the onset of the pandemic, states will need to modify the rates to reflect the unwinding since utilization patterns and average acuity per enrolled member will change. When the continuous coverage requirements set forth by the COVID-19 Public Health Emergency (PHE) ended, Medicaid-managed care programs across the country adopted various approaches to phasing out maintenance of effort (MOE) as a result of changes to the PHE-era continuous eligibility requirements. Phasing out the MOE requirement will ultimately result in members who no longer meet eligibility requirements losing their Medicaid coverage. Further, states are facing a wide variety of circumstances and are implementing diverse approaches to the MOE phase-out. This topic will be of significant interest to all actuaries and stakeholders of the capitation rate development process for Medicaid-managed care programs. Join us as we discuss the operationalization of the PHE unwind while referencing the SOA's research project which models the effects of the unwinding on Medicaid eligibility and population costs. You will learn about the various approaches that different states have adopted to manage the unwinding process, which will be instrumental for accurately pricing managed care rates.