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: Results of a Survey of JRMS members re claims changes due to COVID

Description: Strategic Risk Management was given lower priority in a recent survey of ERM Objectives. This article tells how the author believes that recent events have caused many to shift to a more short term focus and in the future there will be a shift back to a priority for the longer term view that stands behind Strategic Risk Management when the environment settles down and things again seem to be more predictable.

Description: In this article, we summarize inflationary factors that may result in a sharp increase in interest rates and implications for life insurer convexity risk exposure, most notably to dynamic policyholder lapsation. We further provide insights into potential ALM strategies to mitigate this convexity risk. Due to the prolonged low-interest rate environment and low minimum interest rate guarantees offered to policyholders, liability convexity is higher than prior historical periods, which results in life insurers’ ALM positions being extremely vulnerable to short-term interest rate spikes. Convexity mismatches cause issues for life insurers under both rising and declining interest rate scenarios. This means that life insurers are not compensated for taking convexity risk and, therefore, convexity matching should always be considered in the asset optimization process. There are mixed signals from policymakers and financial markets regarding potential inflationary and sharply rising interest rate scenarios. The key takeaway is that life insurers are not compensated for taking convexity risk and it is the right time for insurers to review convexity exposure. There are different approaches available to mitigate convexity exposure through rebalancing of asset positions and hedges within each life insurer’s risk limits.

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: 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: This is a discussion about actuaries, stochasticity and risk management. This article is a response to Max Rudolph's ERM As A Competitive Advantage: Moving Beyond PBA to Add Value The Actuary, April/May 2007.

Description: The article will explore the market dynamics driving asset-intensive reinsurance in Japan, analyze how Japanese insurers are strategically utilizing both block and flow reinsurance to achieve diverse business goals, and discuss key considerations for offshore reinsurers seeking to enter this market.

Description: The direct and indirect effects of the pandemic have impacted many actuaries’ work since the spring of 2020. This article addresses three considerations actuaries should account for when using risk evaluation models which are focused on projecting remote, highly unlikely losses: model effectiveness, asset risk, and insurance (mortality and mortality) risk.