Description: One of the dangers in any sort of modeling, whether for insurance experience or in financial portfolios, is becoming too reliant upon statistics and models, and not keeping reasoned, experienced judgment in sight. This article provides ways to address adverse experience possibilities resulting from misestimation risk.

Description: Review of LTC Industry

Description: Approaches to filing, approving and implementing LTC rate increases impact policyholder behavior regarding retaining/modifying their coverage.

Description: A personal experience of joining the LTC industry and a brief perspective on how to address challenges facing the industry.

Description: Third article in a series on how to use predictive analytics to improve the development of long-term care projection assumptions.

Description: This article discusses the mechanics of a prospective approach to calculating LTC rate increases and compares it to approaches defined by previous model regs.

Description: The editors preview this issue.

Description: Update of the activities being carried out by the Joint Risk Management Section

Description: A general introduction about predictive modeling in insurance applications. Some basic models are discussed, such as Generalized Linear Model(GLM), Calssification and Regression Tree Model. Other models are also briefly introduced, including data clustering, neural networks and support vector machine.

Description: A Mexican actuary discusses his career, the challenges of different insurance markets in different cultures, the value of sharing knowledge across countries and across professions, and the latest public policy regarding solvency models.