Description: Risk adjustment is needed under IFRS 17 to reflect the compensation that a company requires for bearing the uncertainty about the amount and timing of the cash flows that arises from non-financial risk. Companies are also required to disclose the method and confidence level used for the calculation of the RA. However, IFRS 17 doesn’t specify a method and a confidence level, nor does it provide a list of specific risks that are considered to be non-financial risk. Companies need to define them based on their own preferences or existing practices. This article will introduce available approaches and discuss the confidence level approach with potential consideration stemming from industry preferences and illustrative examples.

Description: This article, Spreadsheet Controls Add Risk Resilience, spotlights why spreadsheets have stood the test of time and how they help contribute to an actuary’s success. It also discusses common causes of data integrity issues relative to spreadsheets. And, offers insight into controls that can be utilized to helps actuaries solve these issues and ensure the accuracy and consistency of the data on which they base their analysis.

Description: There will be inflection points in the value of an instrument when interest rates change. These inflection points could materially impact the approximation of value change using ALM metrics. In this part of the seven-part series, I will highlight: • How to identify the inflection points; • the range of rate changes where ALM metrics may be relied upon i.e., the “validity” range, outside of which recalculation of the ALM metrics is required and the potential that one needs to rebalance the portfolio; • a technique to improve on the approximation of value change beyond the validity range; and • a technique to convert non-linear change on the yield curve to be used with duration and convexity.

Description: An introductory article describing how Bayesian statistics has evolved over the past 20 years and why it offers the actuarial discipline powerful tools to better understand and manage risk. Compared with traditional (frequentist) and black-box (machine learning) approaches, Bayesian analysis provides explainable models focused on distributions of estimates instad of simply point estimates.

Description: An introductory article describing how Bayesian statistics has evolved over the past 20 years and why it offers the actuarial discipline powerful tools to better understand and manage risk. Compared with traditional (frequentist) and black-box (machine learning) approaches, Bayesian analysis provides explainable models focused on distributions of estimates instad of simply point estimates.

Description: This is the second part of a 2 part series on Real options analysis (ROA). This article looks into the limitations of using financial option theory when doing real options analysis with projects that are long-dated and uncertain, such as: 1. First-degree homogeneity, 2. Uncertainty must derive from Brownian motion, and 3. Risk neutrality.

Description: There will be inflection points in the value of an instrument when interest rates change. These inflection points could materially impact the approximation of value change using ALM metrics. In this part of the seven-part series, I will highlight: • How to identify the inflection points; • the range of rate changes where ALM metrics may be relied upon i.e., the “validity” range, outside of which recalculation of the ALM metrics is required and the potential that one needs to rebalance the portfolio; • a technique to improve on the approximation of value change beyond the validity range; and • a technique to convert non-linear change on the yield curve to be used with duration and convexity.