Description: In 2018, the Financial Accounting Standards Board (FASB) adopted significant revisions to the U.S. GAAP insurance accounting literature, via Accounting Standards Update (ASU) 2018-12. The title of ASU 2018-12 is “Targeted Improvements to the Accounting for Long-Duration Contracts,” and as a result a common acronym for ASU 2018-12 is LDTI (long-duration targeted improvements).

Description: In 2018, the Financial Accounting Standards Board (FASB) adopted significant revisions to the U.S. GAAP insurance accounting literature, via Accounting Standards Update (ASU) 2018-12. The title of ASU 2018-12 is “Targeted Improvements to the Accounting for Long-Duration Contracts,” and as a result, a common acronym for ASU 2018-12 is LDTI (long-duration targeted improvements).

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: Early in his career, Ehren Nagel, FSA, MAAA, scoured through podcasts and articles about predictive analytics, long suspecting this was a field with potential for him.

Description: Discussion of how to mature value-based contracts between health insurers and provider organizations to improve population health and financial sustainability. Centers around contract parameter consistency, revenue predictability and risk assessment. Intended audience are health plan and ACO actuaries and leaders. Authors are writing from the provider perspective in value-based contracts.

Description: Social Insurance & Public Finance Section council members provide a recap of sessions from the 2021 SOA Health Meeting, with a focus on sessions covering Medicare, Medicaid, the ACA, and public policy. The authors include a description of SIPF Section-sponsored sections, including a session on the ACA and a session on CMS's Direct Contracting Model.

Description: As actuaries in health care, we spend most of our time focused on reviewing claims, enrollment and clinical data. That information is captured while patients are in health care facilities. Yet most people spend only a small fraction of their time in these facilities. This article explores what types of data are available to actuaries the provide a more holistic view of the member so that a members physical and emotional needs, the social determinants of health can be taken into consideration along with their clinical needs. Two uses cases are presented so actuaries can see how these types of analyses can be leveraged to improve clinical, operational, and financial performance of risk bearing health entities. Understanding the customer (member) not just the patient enables actuaries to provide new insights and values to our stakeholders across a wide range of business and risk applications.

Description: This is a brief report that summarizes recent changes in the prevalent medical loss ratio methodologies and also looks at some of the more recent experience of health insurers that filed medical loss ratio reports.

Description: Actuaries are leveraging predictive modeling and machine learning more and more as they strive to provide greater value to their stakeholders. Actuarial standards of practice provide guidance around modeling and data. The world has changed significantly over the last few years, so it is important these models be tested for fairness as well as any statistical biases. This article addresses some of the key issues actuaries need to be aware of as Corporations and society work through the responsible us of this technology and underlying data.