Description: Duration matching is a risk management strategy, commonly used in the insurance industry, where the duration (price sensitivity to a yield curve movement) of an asset portfolio is adjusted to be made equal to the duration of the liability. However, this approach has flaws. In this essay, I note some key failures of duration matching and offer a potential alternative.

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: This article explores how simple climate targets are driving paper decarbonization, which has serious unintended consequences. Risk managers must keep this in mind and choose metrics carefully to do their part in the climate transition.

Description: An update to the risk management readers on what the JRMS is planning to do over 2023 to serve its membership.

Description: Since most cash flows being discounted in the value calculation are dependent on the forward rates, in the key-rate calculation forwards (not spots) should be shifted. I will show that if spots are shifted up/down, they would not necessarily result in forwards being up/down for all the years in the particular key rate, resulting in unexpected results. I will further show how metrics calculated by shifting forwards versus spots enhance the accuracy of the approximation of projected value in various rate environments.

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: Describes the current enterprise risk management, ERM, model for beginners.

Description: Building from the Emerging Risk Survey categories, this article addresses ways that infrastructure can support economic growth from the viewpoint of environmental, financial, geopolitical, societal and technological factors.

Description: Global trends in both technology and regulation are causing U.S. insurers to reflect more deeply on their model risk management frameworks. The world has seen a rapid proliferation of AI-based tools accompanied with an overall increased usage of machine learning models, exacerbating model risk and reducing transparency in an unprecedented manner.

Description: The insurance industry hinges on accurate actuarial assumptions. This session explores how insurers can leverage AI/machine learning (ML) to unlock greater accuracy and granularity in assumption setting, while effectively managing risks, implementing strong governance frameworks, and meeting validation expectations from regulators.