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: Yi-Ling Lin, FSA, MAAA, FCA, started the SOA’s Predictive Analytics Certificate Program to keep pace with the impact big data and predictive modeling is having on the health care industry

Description: 2021 Life Meeting - Session 8A: Use of Electronic Health Records in the Assessment of Life and Health Risks 9.1.21 Recording

Description: Read the Society of Actuaries' latest update about how health care executives view the future of predictive analytics in the health care industry.

Description: Explore wellness programs and their effectiveness within the LTC industry by attending the Considerations for LTC Wellness Programs webcast. You will experience discussions about design tactics and evaluation processes for programs, as well as discovering ways to assist policyholders achieve a sustainable and equitable life. There will also be a conversation about the current regulatory environment as it relates to LTC wellness programs. This webinar will focus on subsets of insured populations that are high risk of claim in order to properly manage care decisions and ensure unfair bias is avoided. Learn how to test for unfair bias and determine best possibilities on how to guard against this when testing is unavailable.

Description: After a decade of traditional actuarial work in health care, David Sotelo was seeking a new kind of opportunity to make an impact. He found it at Collective Health, where he works with a team of actuaries and data scientists that use analytics to streamline health insurance.

Description: Data is everywhere. Health care generates as much as 30% of the world’s data, and new technologies are changing how life insurers analyze consumer information. Actuaries are business-savvy problem solvers. They understand how to leverage the latest technologies and techniques to turn data into actionable insights and solutions for businesses and can communicate those findings to multiple audiences. SOA-credentialed actuaries use predictive analytics to inform organizational and business strategies, with efforts such as identifying chronic conditions in their early stage or determining stress levels through sweat patterns.

Description: This report provides actuaries and other professionals working with risk, data and analytics or program evaluation in the health care space with considerations and frameworks related to the use of determinants of health (DOH) in data and actuarial work streams. Such frameworks can leverage new data sources to enrich health care data analysis to move beyond traditional data elements, such as age, gender, zip code or health diagnosis.

Description: Attend if you are an organization interested in utilizing various kinds of client data to improve the whole insurance sales process, and to develop new applications. Interested parties may include distribution sales force, underwriting, claims, actuarial and finance departments within a typical insurance company, online distribution partners, health care providers and other consulting service providers. The research looks into various use cases, which are typically main issues in modeling in the insurance industry. The research also helps benchmark performance using different languages that may serve as a good reference when best to use a certain language to enhance the development cycle.

Description: Creating a predictive model is one thing, but then taking that model and getting full stakeholder buy-in is another. Learn from presenters' experiences and insights on proving model effectiveness in the long-term care (LTC), life and annuity spaces. Explore various topics such as feasibility, model transparency, fairness and equity, ROI measurement, data assets and compliance, infrastructure and more. By the end of the session, you will gain an understanding of how to navigate the challenges of proving the effectiveness of predictive modeling and obtaining management buy-in.