Description: Discover investing trends across the life and health industry as insurers seek to navigate rapidly changing rate and market environments. BlackRock will present results from its Peer Risk Study, which models industry holdings based on statutory filings at the CUSIP level. Through the Aladdin risk modeling software, expect a production of deep insights into insurer portfolio risk and return characteristics, as well as exploring how they have evolved. Keep an eye out for a partner to present on the evolution from their perspective. Start learning about what is happening on the asset side of the balance sheet across the industry.

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: 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: 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 session will consider how catastrophic gaps in risk management practices contributed to the failure of regional banks in the first half of 2023. Panelists will explore ERM practices and potential corrective actions, based on insurance industry and pension plan best practices, that could have mitigated against the failures.

Description: The CIA, SOA and Joint Risk Management Section of the CAS, CIA, and the SOA sponsored a whitepaper on the application of ERM at a federal government level.

Description: This research report is on the incorporation of flood and other catastrophe model results into pricing and underwriting.

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.

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