Description: The objective of this paper is to provide a practical guide with concrete case studies to help actuaries implement artificial intelligence and machine learning (AIML) to help accelerate the speed of analysis for life and annuity actuarial modeling. We do so by researching the existing literature regarding AIML and its applicability to stochastic modeling and exploring case studies.

Description: This research report on retirement risks and solutions for the middle market was presented in a webcast by the Retirement Income Industry Association. The market was identified, profiled and risk assessed. Then the needs and challenges were assessed and solutions were were offered.

Description: Seeking researchers to analyze long-term risk trends via survey data and develop engaging report formats for broad audiences.

Description: Artificial intelligence (“AI”) adoption in the insurance industry is increasing. One known risk as adoption of AI increases is the potential for unfair bias. Central to understanding where and how unfair bias may occur in AI systems is defining what unfair bias means and what constitutes fairness.

Description: This essay collection examines how changing family dynamics shape retirement security, offering insights on demographic trends, policy design, and actuarial strategy—because retirement is the ultimate family affair.

Description: Seeking researchers to analyze long-term risk trends via survey data and develop engaging report formats for broad audiences.

Description: This report describes and demonstrates a method to understand reputational risk that an insurance company can apply to the unique circumstances of the insurance firm. This method applies a policy-capturing survey with scenario analysis to generate insight into reputational risk from the perspective of a variety of stakeholders. Also included is instruction for spreadsheet-based query and reporting to facilitate the use of the information in the risk management function.

Description: This report documents the work of the UCT with respect to development of an algorithm used to score preferred risk class structures, producing Relative Risk Scores and Prevalences. It is built for both knockout and debit-credit scoring methodologies.

Description: In the context of reinsurance, this paper addresses finding the quota share retention level and the retention limit, with a diffusion process being added to the claim process, that maximizes the adjustment coefficient in the Sparre Anderson model. From Actuarial Research Clearing House, 2006.

Description: This paper provides a new insight to the previous work of Briys and de Varenne [1994], Grosen and Jørgensen [2002] and Chen and Suchanecki [2007]. It shows that if an insurance company follows a risk management strategy, it can significantly change the risk exposure of the company, and that it should thus be taken into account by the regulators.