Description: 2011 SOA Enterprise Risk Management Symposium, Chicago. The stated purpose of this paper is to consider whether a more comprehensive and timely measurement framework for risk exposure is now needed and to examine one possible approach. This paper proposes a new approach to risk measurement that, along with capital measurement and more rigorous oversight, will allow banks an ability to manage risk.

Description: Technology now supports customized non-level death benefits which help consumers optimize their coverage and cost. Creating individual policies and individually pricing them for a level premium quote is the start of personalizing and optimizing coverage and cost for consumers and pricing life insurance policies at the individual consumer level --- a revolution for actuaries.

Description: This article studies the syllabus as a dynamic, interactive teaching tool that informs and is informed by both solutions of complex course problems and student difficulties with these problems.

Description: Understanding Asian Capital Regimes

Description: In this session, attendees will understand the role of AI in risk management and underwriting. You will see insightful case studies highlighting AI-driven techniques for enhancing precision and efficiency in these areas. Additionally, the session will cover advanced AI applications in claim management and fraud detection, showcasing cutting-edge strategies to mitigate risks and streamline operations.

Description: The recent wave of innovation in GenAI has unlocked an entirely new category of AI applications. Whereas AI has traditionally focused on automation and predictions, LLM’s and Generative AI give us the opportunity to create AI applications that act as copilots. This emphasis on contelligence and empowering knowledge workers has already begun to change the way work is done. High expertise knowledge workers such as actuaries will be able to use this wave of AI Apps to make better decisions and dedicate more of their attention to the parts of the role that require domain expertise and judgement. Join Charles Morris, Microsoft’s Chief Data Scientist for Financial Services, as he talks about the latest advancements in this space and the opportunities it creates for expert knowledge workers. Charles Morris is the Chief Data Scientist for Financial Services at Microsoft. Charles has deep expertise in the financial services domain and works with many of the world’s leading asset managers, banks, insurance companies, and financial platforms to develop and execute their AI strategies.Currently, Charles is focused on applying Generative AI to financial services and advising many top financial institutions in building their own copilots and reimagining their businesses.Charles is a data scientist and machine learning engineer by profession and an expert in MLOps. Before joining Microsoft, Charles practiced data science, machine learning, and cloud engineering in the asset management industry. He has been a featured keynote speaker at several prestigious events and forums and is a highly sought after public speaker in the domain of AI and Innovation.

Description: Seeking researchers to analyze long-term risk trends via survey data and develop engaging report formats for broad audiences.

Description: This presentation shares experience and ideas of both AIA Group and AIA China during implementation of the IFRS17 project and will discuss potential impact and outlooks in the domestic market from IFRS 17. This presentation includes a general overview of an IFRS17 implementation project, focusing on changes and requirements, as well as the resources cost of the main challenges and relative resources.

Description: In the context of reinsurance, this paper addresses finding the quota share retention level and the retention limit, with a diffusion process being added to the claim process, that maximizes the adjustment coefficient in the Sparre Anderson model. From Actuarial Research Clearing House, 2006.

Description: Profile of an actuary in a non-traditional actuarial role: focusing on medical cost and analysis, both retrospective and prospective.