Description: The monograph walks the reader through the hindsight, insight and foresight building process while discussing theoretical and practical issues supporting the building of valid forecasts with provenance for each of these schema examples. That is, the analyst can document the iterative ‘profiling change processes’ mindscape and landscape elements by which and through which the successful forecast is built. This kind of forecast construction ameliorates the ‘black box’ problem of generating pattern output without an understanding of the pattern’s creation or contextual meaning that is often seen when using other methods, particularly machine learning and artificial intelligence. This issue is discussed, referencing appropriate thought leaders.

Description: This report captures expert insights from a March 2025 roundtable on how generative AI is shaping actuarial work and insurance industry practices.

Description: This report explores how artificial intelligence can be applied to investment and retirement planning, highlighting real-world applications, risks, and recommendations.

Description: There is value in a framework that allows a smooth transition from a qualitative assessment to a quantitative analysis as entities mature in their understanding of climate risk. In this report, a case study on climate change impact on home prices is used to illustrate a Bayesian network iterative approach to building a model for scenario analysis.

Description: The Canadian Institute of Actuaries and Society of Actuaries Committee on Life Insurance Research, the Product Development Section and the Financial Reporting Section, sponsored this study investigating how the Canadian life insurance industry is utilizing predictive modelling.

Description: Report of the Task Force to Recommend Morbidity Standards for Valuation of Credit Disability. The key recommendation was that a new morbidity standard for valuation of policy reserves be adopted based on the tables developed by the Task Force. The tables are developed from the 85CIDA tables with incidence rates increased by 12%.

Description: This document provides the data specifications for participation in the Group Term Life Waiver-of-Premium Study covering a study period of 1/1/1993 through 12/31/2002.

Description: The purpose of this article is to revise the fuzzy regression portions of earlier studies and to discuss issues related to the Tanaka approach, including a consideration of fuzzy least-squares regression models. From Actuarial Research Clearing House, 2006.

Description: Automobile insurers classify the risks that they underwrite in order to subdivide the portfolio into classes of risks with similar profiles. While some insurers may have sufficient historical data, several others may not have significant volume of experience data in order to produce reliable claims predictions to help enhance their risk classification systems. A database containing a pooled experience of several insurers thereby helps to produce a more fair, reliable, and equitable premium structure for all risks concerned. This paper uses multilevel models to analyze the data on claim counts provided by the General Insurance Association of Singapore, an organization consisting of most of the general insurers in Singapore. The multilevel nature of the data is due to the following: a certain vehicle is observed over a period of years and is insured by a particular insurance company under a certain 'fleet' policy. The authors show how intercompany data lead to a priori premiums and a posteriori corrections to these initial premiums. Specific focus is made in understanding the intercompany effects using various count distribution models [Poisson, negative binomial, zero–inflated and hurdle Poisson]. The performance of these various models is compared the authors also investigate how to use the historical claims of a company, fleet and/or vehicle in order to correct for the premium initially set.