Description: A primer on extreme event modeling and mitigation for practitioners, it covers the complete cycle of extreme event risk management, from identifying experience data sources, to extreme event detection, to modeling and dependence analysis, and finally to monitoring and mitigation.

Description: Global trends in both technology and regulation are causing US insurers to reflect deeper 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. This rising tide of AI means that it is imperative for US-based insurers to address these emerging risks within their Model Risk Management (MRM) frameworks. Regulation also continues to evolve in this space: in Canada, the Office of the Superintendent of Financial Institutions (OSFI) revised Guideline E-23 to instill more detailed model risk management standards; in Bermuda, the Bermuda Monetary Authority (BMA) has published CP2 to add increased scrutiny on the data and models used by insurers. Insurers must react: MRM frameworks require prudent revisions to reflect these ever-changing landscapes of risk. Reassessing the core pillars of MRM frameworks - risk measurement, model development, validation, monitoring, and governance – is key to understanding the consequences of these evolving market changes on insurers’ risk profile. Overall, the inclusion of these new tools into the world of insurance necessitates a thorough examination of insurers’ MRM frameworks in order to align these new risks with core MRM principles. In this session we will: - Reflect on recent drivers of change and how they should be considered in the context of MRM - Explore best practices as it relates to MRM frameworks in the context of current global trends - Describe challenges, success stories, and lessons learned relating to recalibrating and embedding MRM frameworks

Description: The life insurance industry is facing a rapidly changing landscape, with several emerging risks demanding the attention of actuaries and industry professionals. While actuaries commonly examine historical experience to guide our estimates of future outcomes, we are often faced with evidence that some of the forces that dictated past performance no longer persist and in some instances may even turn into contrary forces. This session aims to explore the key challenges and opportunities presented by risks with limited historical context, and discuss strategies to effectively manage them. We will delve into critical emerging risk areas, such as interest rate and asset risk, the rise of AI, climate change, predictive analytics in underwriting, and more. The session will feature speakers who are experts in managing risk, as well as results from interviews with top corporate risk professionals, such as CROs and ERM leads from major insurance and reinsurance companies. Attendees will gain valuable insights into emerging risks and practical strategies to navigate the evolving life insurance landscape.

Description: Amid the growing adoption of AI/ML models for underwriting and pricing, Life and Annuity carriers are facing increasing regulation in North America on Model Risk Management (MRM) and the use of AI. Colorado has set a precedent in the US by requiring reporting in June 2024, with other states looking to follow suit. To ensure compliance, Chief Risk Officers and Heads of MRM, working with their business partners, will need to evolve their MRM and AI risk frameworks, enhance model validation capabilities, and strengthen governance. This session will present: - Key trends and challenges faced by carriers amid increasing model landscape complexity and regulatory expectations - Regulatory outlook and implications for carriers' MRM and AI risk programs - An approach to enhance MRM and AI risk frameworks, including specific model validation program updates to address the unique risks of AI/ML models - Opportunities to enhance both MRM validation effectiveness and efficiency through the adoption of more risk-based approaches, smart sourcing, and automation - Case studies of how leading carriers are evolving their MRM and AI risk programs Upon attending the session, the attendees will develop a good understanding of increasing regulatory expectations, the required MRM and AI risk framework enhancements, and approaches to design and execute an effective MRM validation program in a cost-efficient manner.

Description: This is the SOA website page displaying the table of contents for Risk Management: The Current Financial Crisis, Lessons Learned and Future Implications series of essays.

Description: Update of climate risk related governance and disclosure.

Description: Enterprise Risk Management incorporates integrated risk management due to the fact that the majority of company failures result from multiple correlated causes. Sites findings from Mercer study

Description: A discussion of the pillars required to build the needed paradigm for insurance company risk management. From The Actuary Magazine April 2005

Description: This is an editorial article on risk management books.