Description: As artificial intelligence reshapes the actuarial landscape, this panel will explore the critical aspects of change management necessary for the successful integration of AI technologies. We will discuss how to effectively embrace AI in the workplace and address common challenges and resistance to change. Join us for an engaging discussion on navigating this transformative journey and empowering actuaries to harness the full potential of AI in their work.

Description: We will first present a few very practical use cases of GenAI tools that could help the daily life of an actuary. Then we will demonstrate the power of these tools in coding (e.g. Cursor, but also ChatGPT) - improv style. Taking a suggestion from the audience - a publicly available dataset - we will demonstrate how you can ask questions to a large language model, which will write code and provide the insight you are looking for.

Description: This session will delve into the valuable lessons learned from recent accounting change implementation, covering both model and process optimization. Attendees will gain industry knowledge as we explore optimization decisions made by others, highlighting both successful strategies and areas for improvement. We will discuss key decision points throughout the entire actuarial process, including data manipulation, actuarial calculation engine, and post-model reporting.

Description: Insurance companies are substantially transforming their finance operating model. This is mainly trigged by the prevailing changes in the insurance regulatory landscape that are leaning towards principle-based reporting and valuation, which is leading to a significant increase in the effort needed for regulatory and management reporting.

Description: You’ve written the position papers, updated the models, and designed the required disclosures, but you may be wondering how to explain the results during interim financial reporting periods to company management as well as other stakeholders. This session will explore ways to adapt existing management reporting and offer ideas for new metrics. We will explore various methods for analyzing DAC amortization patterns, market risk benefit reserve patterns, and Liability for Future Benefits (LFPB) movements. In addition, this session will explore ways to integrate changes in LDTI with business planning and other broader business issues such as product pricing considerations and reinsurance strategy.

Description: Virtual - Session 1A: From Actuary to Data Scientist - Career Journeys into AI

Description: Virtual - Session 2A: Building and Using an AI Simulation Model

Description: This session introduces you to the next level of gen AI: AI Assistants (also known as Custom GPTs, Gems, or Bots). An AI Assistant is a specialized, tailored version of a Large Language Model (LLM) that allows the user to produce a persistent, pre-programmed tool designed to handle complex, repetitive professional tasks with guaranteed consistency, accuracy, and alignment. We will move beyond casual prompting to explore the mechanical architecture required to build reliable, high-stakes assistants for a variety of applications.

Description: Artificial intelligence brings immense opportunities for productivity gains—and valid concerns. It can both support innovations in insurance products and in the customer experience as well as enhance our profession’s work. Actuaries share a responsibility for caution and professional judgment to use it without jeopardizing the fair and equitable treatment of individual consumers and the principals we serve.AI creates significant challenges for consumers: opacity, reliable accuracy, privacy, and verification of personal data. The Academy and its members have been working to educate and inform stakeholders, insurance commissioners, and regulators toward improving the transparency of algorithms that underlie the use of AI by insurers, to explain how the algorithms can be used to achieve equitable treatment, and to identify the issues and trade-offs related to ensuring consumer protections. We must amplify the actuarial perspective on how adequate disclosures, documentation, and governance of AI can help protect users. This session will examine how we can govern and support the evolution of better practices. We will discuss how AI is addressed via standards such as ASOP No. 56, Modeling, and other guardrails that are being developed to best utilize AI’s real-world potential and fulfill our professional responsibilities.