Description: This paper explores the flexibility of kernel estimation as a means of nonparametric graduation and relates it to moving-weighted-average graduation. From Transactions of Society of Actuaries 1995, Vol. 47.

Description: Focusing on the topic of Principle Based Reserves (PBR), the SOA offers on-demand education. The PBR series consists of ten micro-lessons providing foundational education on PBR and requirements of VM-20.

Description: This paper addresses the need for obtaining further information about the differences in life insurance persistency or lapsation among companies during the first fifteen years from issue. It also introduces the statistical technique of cluster analysis From Transactions of Society of Actuaries 1981, Vol. 33.

Description: Feature article discussing how to do a model update.

Description: Learn how modernization of data, models, and technology are influencing workflows. This webcast will address how workflows are changing in response to new regulatory requirements and the impacts the changes have on modeling and end-to-end future state operating models. Industry leading actuaries will discuss: How team collaboration can increase quality and speed of reporting to internal and external stakeholders How to strengthen controls and compliance frameworks across finance and actuarial departments How to modernize actuarial input/output for strategic analysis and insights How to attract and retain top talent by improving opportunities for actuaries There will also be dedicated time to ask questions of those who have made the transition.

Description: Recent developments in automation capability have opened the door to improvements in the way that companies are able to monitor compliance with Internal Revenue Code (IRC) Section 7702. Further automation of Section 7702 testing allows for less input, more policy testing, and significant reductions in manual processes and risks associated with them. As technology has improved, and computing power become virtually limitless, the insurance industry can take advantage of these new technologies to improve and enhance 7702 capabilities. The result can be an easier, faster and more comprehensive process that will be more scalable across products. By attending the session, you will: - Understand the basics IRC 7702 calculations and computational limitations on traditional solutions. - Identify the features that make low-code/no-code solutions unique and their uses in an actuarial context. - Apply the pros and cons of low-code/no-code (LCNC) solutions in a 7702 context.

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.

Description: With many complex regulatory changes on the horizon as well as pressures to ensure model accuracy from auditors, regulatory requirements and new actuarial standards of practice, the importance of robust model validation is coming to the forefront of actuaries’ minds. What was previously a day-two task for many companies is becoming just as important as model development! In this session, you will hear from those that have been deeply involved in building model validation frameworks and tools in responses to regulatory changes GAAP Long Duration Targeted Improvements (“LDTI”) and Principles Based Reserves (“PBR”).

Description: This article is the first in a series of articles on insurance applicant mortality risk analytics. From Small Talk Newsletter, Issue 37, January 2012.

Description: The purpose of this paper is to understand characteristics of a household that drive life insurance demand with more sophisticated analytical techniques. The analysis is based on the Survey of Consumer Finances data, a probability sample of the U.S. population. Household demand of two types of insurance, term life insurance and whole life insurance, is examined jointly. We model both the frequency and the severity of demand for insurance building on the work of Lin and Grace 2007 by using covariates that they developed.