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: Come learn from a panel of LTC industry professionals as they discuss setting goals for LTC wellness, measuring success of the programs, and integrating them with other LTC process (e.g. assumption setting) in an effort to create sustainable programs.

Description: There is increasing industry interest in applying behavioral science to optimize product design decisions and improve outcomes for both insurers and their customers. With a growing set of options within product designs, predicting consumer behavior continues to get increasingly complex. Join this webcast for an overview of key behavioral economic concepts. Key insights will be shared from two SOA projects that explore how behavioral economic techniques can be used in various parts of the life insurance new business process and inforce management.

Description: The frequent use and complexity of today's actuarial projection models has increased the importance of having efficient models. Model optimization can reduce both cloud costs and overall end-to-end clock times, thereby allowing companies to do more with less such as reducing close times, increasing controls, enhancing analysis, doing more complicated calculations, and/or improving employee workloads during the close. From design and data to execution and audit, come explore techniques that can be applied throughout the actuarial modeling process to optimize actuarial models for improved run-time, accuracy, and reliability. There will be a focus on techniques that don't rely on model compression. Topics covered include model design pitfalls, data handling, improving convergence on asset-liability projections, strategies for interacting with the cloud, and other tips for optimizing actuarial models.

Description: Learn from panelists from different companies as they come together to discuss their experiences.

Description: Asset liability management is an important task for any insurer, where tools like Excel play an important role from an analytics perspective. Dashboard tools like Power Bi and Tableau can supercharge an organization’s ability to perform ALM with real-time precision and monitoring of risk/imbalances. The dashboard can provide insights into potential risks posed by asset allocation and concentration, allowing for informed decision-making to mitigate those risks. The presenters will walk the audience through an example of ALM use case, including how to build key performance indicators such as cash flow, asset allocation, and risk exposure. Additionally, we will demonstrate how these types of dashboards can be customized to fit the specific needs of your organization.

Description: This is the first in a series of calls for essays on the impact of AI on mortality and longevity. For this call for essays, we are interested in the impact of AI on mortality and longevity modeling, forecasting and prediction.

Description: CMS has required hospitals to publish their chargemaster rates, cash discounts and negotiated rates as of January 1, 2021. Our panel is comprised of a data strategist, an executive from a large hospital system and an actuary.

Description: Come discuss modeling costs and its governance, as well as introduce some platforms for more granular asset modeling.

Description: "As digitization and automation rapidly progress in today’s life and health industry, issues with misrepresentation during the insurance application process are also becoming a growing concern for insurers around the globe. A recent survey finds that misrepresentation in application forms costs the average insurance customer an estimated 5% to 10% in higher premiums. In order to reduce this risk, insurers must find and correct areas of misrepresentation, consult post-issue sampling, review the automated underwriting processes, and monitor the quality of financial advisory firms. Learn how predictive disclosure modeling detects and reduces misrepresentation by harnessing readily available underwriting data to analyze issues, helping insurers understand various drivers for disclosure rates and areas of misrepresentation.Advantages of this modeling to various stakeholders in the life insurance journey include improved risk selection, claims experience, and reinsurance terms for insurers. For customers, it leads to increased certainty of coverage, payout of the claim, and ultimately lower premiums on average. By the end of the session, attendees will understand: The disclosure modeling process at a high level The technical details of a standard approach to disclosure modeling: data cleaning, standardization, visualization, and predictive modeling Success stories about how predictive disclosure modeling has impacted insurers"