Description: The health insurance industry has historically used several factors to develop premium rates. Many of these, e.g. gender rating, have been largely eliminated from health insurance rating practices by regulations as the Patient Protection and Affordable Care Act (ACA) because they were determined as inequitable. However, several other factors still remain as differentiators in premium rates charged to individuals and groups. In conjunction with the SOA, researchers studied whether there could be ‘ghost’ rating factors, like race, ethnicity, or socioeconomic status, that are inherently included in some of these remaining allowable factors. Review results and opportunities for future research. By attending this webcast, you will be challenged to think about traditional rating factors in a different way. Rather than focusing on whether certain factors are sound based on the underlying claims cost, this session will focus on whether or not these factors are impacting certain socioeconomic or racial/ethnic groups disparately.

Description: "Can you answer the question 'what are the chances we will lose more than $1 million next year?' without saying 'it depends'? If you miss a projection, can you quantify the chances that the miss was due to random variation vs. an incorrect projection? ten in as presenters demonstrate how to answer these questions and others using total risk analysis. Total risk analysis includes quantifying both the random variation risk and the projection risk associated with actuarial functions like pricing and reserving. After attending this session, you will be able to describe total risk analysis, apply total risk analysis to many actuarial functions."

Description: "Examine the impact of traditional deductibles on health care equity and the need for innovative plan designs. You will learn about the limitations of consumer-driven health care costs broadly today, as well as alternative cost-sharing approaches that have been successful in driving consumerism without exposing members to high costs. By attending the session, you will be able to: Have a clearer understanding of the issues surrounding deductibles Be equipped with practical ideas for creating more equitable and effective cost-sharing solutions Assess the feasibility and potential impact of implementing these solutions for your own organization"

Description: In this presentation, actuaries and data scientists from Cleveland Clinic and Milliman discuss the development of a sepsis prediction model using machine learning. Presented with a unique challenge of handling massive amounts of data for near real-time risk scoring, the team took their model development to the cloud and delivered a product in less than a week through a unique virtual engagement.

Description: ReMark's Global Consumer Study delivers 10 key insights to empower customers. Insurers can design products that meet customers' needs and enhance client experiences and add significant value to their business. At the same time with new products being launched seemingly continuously, it is important to take a step back and assess risk throughout the product management cycle.

Description: In discussing the contemporary reactions to this regulation, as well as how EU-based insurance firms adapted to the shift, this segment will invite us to question our assumptions on the role of gender-based pricing in the future of the industry. In the latter half of the presentation, we will delve into the challenges faced by LGBTQ+ individuals when accessing life, health, and auto insurance.

Description: This article summarizes a survey on career satisfaction and advancement conducted last fall via FutureRisk.org. The survey asked actuaries about topics ranging from their current job situation, employer and professional aspirations to job satisfaction, career advancement activities and training received via various resources.

Description: This is the editors column.

Description: View the Archive Fall 2016: Life Finance and Valuation Exam (Canada).

Description: Fall 2015 Archive Syllabi