Description: The barrier between humans and machines continues to blur, but curiously, this may have been prediction thousands of years ago in ancient myths. This article looks to how some of the early legends are becoming manifest in modern technology, particularly in the area of elder care. From automation, to humanoid assistants, to mind clones will the age of technology bring a new utopia?

Description: As the insurance industry continues to evolve due to a pandemic and rapidly changing economic and regulatory conditions, the role of data scientists and actuaries has become increasingly important. In an interview with the Atidot data science and actuarial team, we discuss what it is like to work at an InsurTech, how data scientists and actuaries can collaborate, and look at some concrete technical examples of where the innovation is having an impact. This article explores what collaboration can look like and how the role of data science and actuary may evolve in the InsurTech industry in the future.

Description: The article urges actuaries to see AI not just as a tool but as a strategic partner, drawing parallels to past transformative technologies like the printing press. Using NAIC survey data, it shows AI adoption is surging in health and auto insurance, lagging in life. It outlines AI’s potential to boost productivity, improve data quality, and enhance contract analysis, while warning actuaries to master AI before others use it to evaluate their work. Ethical standards demand transparency and fairness, making responsible AI use part of professional duty. Historical examples—like James C.H. Anderson’s 1970s cash flow testing breakthroughs—highlight how visionary actuaries can redefine the profession. The article applies Harvard professor Jeff Bussgang’s “hair-on-fire” innovation lens, suggesting AI-powered, urgency-driven insurance products, akin to Y2K coverage, could revolutionize offerings. It calls on actuaries to address protection gaps, discrimination, and industry opacity through AI-enabled fairness. The message: courage, creativity, and proactive adoption will let actuaries shape—not just survive—the AI-driven future. The closing reflects on the author’s tenure with the SOA Reinsurance Newsletter, framing this as a final, forward-looking call to action for actuaries ready to lead in a transformed insurance landscape.

Description: The proposed session will introduce Outcome Based Risk Sharing Arrangements (“OBRSA”) between health insurance payers (“payers”, including insurance companies, health plans, sponsored employers, and government programs) and pharmaceutical manufacturers (“pharma”), and it’s intended to meet the needs of actuaries who focus on pharmacy benefits and risk sharing arrangements. The covered content will include (1) the background of OBRSAs, definitions, stakeholders, and OBRSA’s role in shifting the system from volume-based toward value-based; (2) conflicting perspectives about OBRSAs between payers and pharma (cultural and methodological); (3) identification of incentive gaps between payers and pharma, and incentive alignment between them; (4) barriers to implement OBRSAs; (5) limitations and considerations of OBRSA implementation; and (5) hypothetic OBRSA examples.

Description: Big data and machine learning have been making headlines across industries everywhere, how will it impact the world of actuarial science?

Description: Recurrence relations arise naturally in life contingencies for 2 reasons - the aggregate law of mortality, which relates the distribution of the future life times of 2 insureds, if one of them and the other is that most life insurance products can be constructed as a portfolio of 2 basic product types. We use the above simple idea and the extra freedom provided by the fractional age distribution to reveal a structure behind some common recursions. The structure has obvious pedagogical value. More interestingly, a software based on it has been implemented which facilitates actuarial computing.

Description: A discussion on supervised learning--the class of machine learning where a model is trained to produce a specific result for a given input.

Description: Actuaries have the opportunity to transform to a new role that utilizes predictive analytics and new data sources such as epigenetics, to better humankind.

Description: The purpose of this paper is to define a predictive model, based on known system attributes, for assessing risk associated with information systems.