Description: This article discusses the rationale behind having premiums for long term care insurance that vary by gender. Differences in LTC morbidity and practical aspects of gender distinct rates are discussed.

Description: Mortality Credibility and its use within VM-20.

Description: Proposes an approach to develop dynamic assumptions for living benefits using a combination of available experience data and predictive modeling techniques.

Description: A question from a reading regarding the accuracy of a comment from the December 2016 issue of The Financial Reporter article titled “Negative GAAP Term Insurance Reserves—to Floor or Not to Floor?”

Description: A discussion of the FASB's Sept. 29, 2016 issued exposure draft on targeted improvements to accounting for long- duration insurance contracts.

Description: Continued look at unlocking of traditional contract valuation assumptions, this time examining the frequency of true up for actual experience.

Description: This article will focus on introducing where IFRS17 differs from US GAAP conceptually, and key aspects of this paradigm shift from actuaries’ perspective.

Description: VM-20 requires prudent estimate assumptions that are based upon a combination of company experience, industry basic tables and prescribed margins. VM-20 has requirements on how company experience is defined, and also requires that additional margins be established if the actuary does not consider the prescribed margins to be adequate.

Description: An introduction of predictive modeling techniques that are applicable to insurance industry, including generalized linear model (GLM) and classification and regression tree model(CART). Other models such as data clustering, neural network, and support vector machine (SVM), are also briefly discussed.

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.