Description: We highlight a new approach leveraging predictive analytics to identify high risk and rising risk opioid users for more effective screening and follow-up care.

Description: Reviewing a text covering multiple statistical modeling topics: e.g., generalized linear models, decision trees, clustering, using the statistical language R.

Description: The SOA, with SCOR as the researcher, completed an experience study of post-level term (PLT) lapse and mortality. In the first part of this session, the presenters will cover the key findings of the traditional analysis regarding the shock lapse, the PLT lapse and mortality experience. The remainder of the session will focus on the results of the predictive modeling, which will provide further insights into policyholder behavior in the post-level term period.

Description: Gather with members and non-members in the China actuarial community to discuss recent topics and related issues in areas such as macroeconomic sharing, pension, investment, product strategy, and more.

Description: Second article in a series on how to use predictive analytics to improve the development of long-term care projection assumptions.

Description: The article recaps existing ideas for assessing credibility and describes questions remaining to be answered.

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"

Description: Electronic Health Records are here to stay. Take a deep dive into the world of electronic health records and how the industry is poised to utilize this new form of digital medical data to transform the way policies are underwritten and ultimately, transforming the client experience. Listen to industry experts speak about what they are doing to use this data most effectively and how this ultimately develops into ground-breaking solutions for the industry.

Description: Following her first 100 days as the CMS Administrator, Chiquita Brooks-LaSure released her six strategic pillars for the agency. The Center for Medicaid and CHIP Services (CMCS) followed these pillars and laid out their priorities for states under the Biden-Harris administration. With these priorities established, recent 1115 submissions from several large states, including California, Massachusetts and New Jersey, may give insight to how CMS will operationalize their vision under this program authority. This session will include presentation from state policy staff who have led recent 1115 waiver proposals.

Description: Learn more about the predictive modeling that was applied to industry data for the lapse and mortality experience in the post-level term period. Novel approaches were taken to model the shock lapse, subsequent lapse, and mortality experience. Observe a demonstration of the Tableau tool, which was built to allow users to analyze data on their own.