Description: Deciding where to spend that next dollar of capital is at the heart of financial management. Executive teams regularly grapple with decisions on whether to purchase a new Enterprise Resource Planning (ERP) system, invest in growing a distribution channel, expand into a new geographic area, or develop a new product, among many. The great news is there is no shortage of sound financial theory and logical rationale for making these transformational decisions. Yet business literature is filled with examples of decisions that did not meet expectations, sometimes materially missing the mark when comparing experience to assumptions. This is particularly the case with mergers and acquisitions, where multiple studies have shown that a sizable majority of such transactions do not achieve their intended outcomes. While some of the disappointing returns are attributable to random chance and unfortunate circumstances, a material number of them can be traced back to cognitive issues that arose during the decision-making process. Mental shortcuts or heuristics taken by individual decision-makers in evaluating information, as well as organizational dynamics such as groupthink both contribute to sub-optimal choices involving significant outlays of money. Being aware of these and having established protocols to mitigate against them can substantially improve decision-making around capital allocation and reduce misallocation of funds. In this session, the panelists discuss several common cognitive biases that can adversely impact the capital allocation decision process, introducing the notions of time, accounting convention, positivity, hierarchy, and social proof in describing them. Historical case examples of sub-optimal capital allocation are then explored, identifying the contributing behavioral factors including the simultaneous confluence of multiple factors. The panelists will close the session with several suggestions for attendees to consider for incorporation into their decision-making processes. At the conclusion of the session, attendees will be able to: - Learn common cognitive biases that impact capital allocation decisions - Differentiate which biases impact different aspects of the capital allocation process - Build awareness of biases affecting capital allocation decision models - Mitigate cognitive biases present in decision making processes

Description: This session will highlight the growing significance of climate risk for insurance companies, emphasizing how to prepare for regulatory requirements as well as the impacts on financial stability and operational resilience within the industry. Attendees will gain insights specifically addressing climate risk within insurance operations including enhancing governance structures, ensuring regulatory compliance, identifying and monitoring metrics and key risk indicators, and conducting scenario analyses. Through real-world case studies and perspectives from both life and property and casualty practitioners, participants will leave equipped with practical strategies to navigate the complexities of climate risk management, foster transparency and accountability, and effectively address the urgent challenges posed by climate risk within their organizations. Learning Objectives: - Understand the evolving landscape of climate risk and regulatory requirements for climate risk disclosure - Gain insights into effective approaches and current best practices that actuaries and risk modelers may use in performing qualitative and quantitative climate risk scenario analyses - Learn practical strategies for integrating climate risk considerations into insurance operations

Description: The National Association of Insurance Commissioners (NAIC) project for the transition to a new real-world economic scenario generator (ESG) prescribed for principle-based reserve and capital calculations selected a vendor in the fall of 2020. The American Academy of Actuaries and other interested parties have been assisting the NAIC in this transition. Over the past four years, extensive analysis, model validation, and comparison work has been done. There have been many updates on the project but few opportunities to obtain an in-depth understanding of the new features of the new ESG and its impact on reserves and capital. Practitioners are very interested in the questions: - How different are the scenarios from the Academy/Society of Actuaries ESG and the new NAIC ESG? - How different are the models and techniques used to create the scenarios in both generators? - Is there a significant difference in capital and reserve requirements for model office tests between the two ESGs? - Are there concerns with the new NAIC ESG? The session addresses each of these questions in detail. At the conclusion of the session attendees will appreciate the key differences between the model structure and scenario performance of the two ESGs and will understand the differences in capital and reserve requirements for model office tests across the two ESGs. Attendees will also learn how the initial yield curve fitting differs between the models, about fund mapping considerations, and the interpretability of parameters in the new NAIC model.

Description: Joint Risk Management Section chairperson's corner, June 2023

Description: Article discussing the benefits of the Chartered Enterprise Risk Analyst, CERA, credential.

Description: Analyze the market volatility behavior in context with historical extreme events during this webcast. There will be a focus on understanding volatility clustering and relationships, both contemporary and temporal, in addition to key economic and capital market variables. You'll also learn from a comprehensive attribution analysis, which uses economic data, asset data, retail investor data and event data as explanatory variables. Dive into investment-related Reddit comments used to capture features of retail investors and tree-based models, including Random Forests and Gradient Boosting Machines to justify changes in volatility modeling. Expect this webcast to end with an example of liability-driven investment optimization that illustrates the potential impact of increased volatility assumption, how to adopt stochastic volatility models, how to reflect volatility clustering and return jumps.

Description: Come discuss modeling costs and its governance, as well as introduce some platforms for more granular asset modeling.

Description: Introduces the concept of total risk analysis, a methodology used to answer questions like "what are the chances we will lose more than $1 million"

Description: This survey tracks the relative rankings of risk managers about emerging risks across time. It is the 18th survey of emerging risks sponsored by the Casualty Actuarial Society (CAS), Society of Actuaries (SOA) and Canadian Institute of Actuaries (CIA), administered by the Joint Risk Management Section.

Description: This report looks at identifying drivers of systemic risk in China’s insurance industry and develops a measurement method for systemic risk as well as systemic risk dependence between the insurance industry and other industries.