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: Focus on Accelerated Underwriting (AUW) in the life insurance industry, which is an expedited underwriting process that utilizes predictive models. Expect to address the challenges in designing the process, from modelling to performance monitoring. Additionally, you'll address risk management, particularly in mortality and proxy discrimination andhighlight the role an actuary can play in the AUW process, as well aswhat they should know to contribute effectively.

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: Session 4B: Impact of GLP-1 Drugs on Health Care Cost Trend and Clinical Outcomes

Description: As health insurance self-funding becomes more popular among smaller group sizes, risk is evolving for the MGUs, stop loss writers, and reinsurers that cover them. Assessing more small groups at lower attachment points means rethinking traditional stop loss underwriting techniques.

Description: Carol McCall led three teams – predictive analytics, health economics and outcomes research, and personalized medicine. The “river running through them” was that they all leveraged data. Her predictive analytics team eventually built a broad portfolio of models with some of them having a significant impact on Humana’s top and bottom lines.

Description: The SOA provides information about the actuarial career path in health care and predictive analytics. Throughout 2016, we will share more about actuaries who are tackling some of the industry's biggest challenges and hear from top employers in healthcare analytics.

Description: Read the May 2020 issue of Actuarial Technology Today published by the Technology Section. Newsletters provide practical information for the working actuary, articles on trends that impact sections and news about section activities.

Description: Describes the predictive analytics revolution taking place in the insurance industry

Description: Overview on current trends in medical practice impacting the LTC insurance business with a focus on dementia, risk stratification, and predictive modeling.