Description: You’ve built or updated a predictive model. Is it any good? How can you interpret and understand its predictions? How does it compare to alternative models? This session will look at traditional and non-traditional ways of validating predictive models, with examples from case studies.

Description: Regulatory change and increased focus on internal risk management are driving a renewed interest in model efficiency. In this session, we will review several new and existing tools, that show significant promise for advanced modeling of equity linked products. These include: • Clustering • Use of unique--and potentially a different number of--scenarios for each policy • Semi Monte Carlo (SMC) – this is a proprietary technique that is similar to a combination of Monte Carlo and numeric integration • Using a neural network approach to optimize some of the more complex and manual aspects of clustering and improve the fit of the clustered model • Combining SMC with the use of unique scenarios per policy

Description: Read the October 2019 issue of CompAct, published by the Technology Section of the Society of Actuaries.

Description: This literature review provides insights on emerging technologies that interact with the actuarial profession within the space of microinsurance for the purpose of establishing a frame of reference for actuaries to use in their work. Furthermore, it intends to spark readers’ interest in, and create a vision for, how microinsurance and its associated technologies may impact the actuarial industry in the future.

Description: Presenters will discuss mortality improvement as it applies to various lines of business with an emphasis on how individual life findings can be used to fine tune group life assumptions. In particular, it is important to know that there is not a single percentage of annual mortality improvement. Rather, experience shows that the rate of mortality improvement varies by factors such as attained age and target market.

Description: Predictive models can improve the traditional actuarial assumption-setting process. Data science techniques can provide deeper insights into experience through their ability to identify key drivers, rank importance and account for interactions. The presenters will cover ways in which companies can utilize predictive analytics to set assumptions, including the various methods available and practical approaches for implementation. They will also discuss the advantages and challenges of using predictive models for setting assumptions for life, annuity and disability products.

Description: There are two main equity release plans for retirement financing: reverse mortgage plan and home reversion plan. Both plans entitle the home owners to release cash from their properties without leaving their home. In the lease buyback scheme (LBS) recently introduced rin Singapore, the home owner sells the tail-end of the property lease to the government in exchange for a cash payment upfront. Unlike the two main equity release plans, the LBS only allows the owner to stay in the property during the front part of the lease but not for life. In this paper, we propose a hybrid home equity release plan that incorporates both features of the home reversion plan and the LBS. We provide an actuarial framework to analyse the pricing of the hybrid plan. Some numerical illustrations are presented to show the actuarial values of the plan under different parameter choices, such as lease period and portion of property values sold. The hybrid plan provides enhanced flexibility to plan takers to meet their retirement needs.

Description: The article provides an introduction to some of the key limitations that the Internal Revenue Code imposes on business uses of life insurance, focusing on the limitations under Section 264(a) on business deductions for premiums and interest expenses related to life insurance, the similar limitations under Section 264(f) for unrelated interest expenses of businesses that own life insurance, the limitations under Section 101(j) on the excludability of death benefits under employer-owned life insurance contracts, and the recently-enacted rules for life settlement transactions.

Description: Regulatory change and increased focus on internal risk management are driving a renewed interest in model efficiency. In this session, we will review several new and existing tools, that show significant promise for advanced modeling of equity linked products. These include: • Clustering • Use of unique--and potentially a different number of--scenarios for each policy • Semi Monte Carlo (SMC) – this is a proprietary technique that is similar to a combination of Monte Carlo and numeric integration • Using a neural network approach to optimize some of the more complex and manual aspects of clustering and improve the fit of the clustered model • Combining SMC with the use of unique scenarios per policy