Description: The mismatch between how interest rate impacts the value of assets and liabilities could have material negative impact to companies’ earnings and surplus. To quantify and mitigate the impact of such mismatches, companies have used matching a combination of duration and convexity. I will review these measurement techniques and their limitations.

Description: This article provides an introduction to group supervision and group capital and its importance in today's increasingly global insurance market. Additionally, the article examines the various methods used in practice for calculating group capital and the factors that companies should consider as they develop their group capital management strategy.

Description: The article is authored by the chair of the Joint Risk Management Section and provides an update of recent changes relevant to members of the council, as well as interested non-members.

Description: Description of the mathematics involved when looking at low probability events within a company from the perspective of the C-Suite. The accumulation of small probability events leads to a much higher probability of at least one of them happening in a given period.

Description: Regular update provided by the Chair of the Joint Risk Management Section on initiatives put forth by the section council for the current year.

Description: This article will highlight the issue that the sum of key-rate metrics does not add to metrics derived by parallel shift to the entire curve, even at very low shift size. Additionally, in the article I will outline how to define a single rate change to be applied to a key rate (or the entire curve) since the rate changes are generally not level or parallel.

Description: By attending the session, you will learn: - Different perspectives around what FP&A is used for (e.g., strategic planning, performance measurement, management compensation, liquidity management, etc.) and why - Challenges leaders have faced and how they are being addressing - How recent regulatory, accounting, and technological change has impacted the FP&A function - Objectives for various organizations around both new analytics for business management, efficient production of forecast results, and potential for faster 'top down' forecasting

Description: Observe how design thinking can be used to address emerging uncertainty in insurance. (Design thinking is a non-linear, iterative process teams use to understand users, challenge assumptions, redefine problems and create innovative solutions to prototype and test.) According to Fostering Innovation: A Guide for the Actuarial Profession, there is a need for more innovation in the actuarial profession. “A benefit of working in large, well-established organizations is that these workplaces have many problems to solve, but offer many resources, as well as a network of people for collaboration. However, it is interesting to note that the stability and predictability of cyclic work may also be seen as a negative by workplace employees, especially concerning creativity and innovation.

Description: Examine how investment portfolios have been changing over recent years with a panel of industry experts from the life insurance industry, and learn what lies ahead. This will be a highly practical session, with real-life case studies referenced as much as possible.

Description: Modeling Approaches and Challenges focuses on approaches to real world simulation and the challenges and considerations in real world simulation. Topics include: A frequency domain approach to build realistic multi-horizon scenarios. (Ortec approach) Cascade models structure linking models for major asset classes and economic variables. (Moody’s approach) Overview of models, calibrations & approaches within the context of different use cases. Deterministic & stochastic approaches. Importance of model re-calibration flexibility. We will also discuss specific insights into considerations and challenges in real world simulation, which include topics like: Setting capital market assumptions and/or calibration targets. Assumptions about correlation and causality. Calibrating the model to capital markets assumptions. Validating the model against capital market assumptions. Role of history, market data and stylized facts. Importance of back testing. Calibrating the model to multiple investment horizons. Inclusion of alterative asset classes such as private equity, infrastructure, and direct real estate. Associated issues of limited data, illiquidity and greater uncertainty about calibration targets.