Description: The actuarial profession is changing rapidly and the skills needed to be successful are also changing. In this session, we will debate key topics and questions, such as: What is the predominant future career path for actuaries? Specialists or generalists? Does the actuarial profession have a meaningful value prop outside our core domains e.g. insurance? What skills are needed for the actuary of the future? What’s the best approach to improve actuarial storytelling to non-actuarial audiences? What’s the role of actuaries to managing and predicting emerging trends and assumptions? What is the role of actuaries in relation to development and ownership of advanced modeling? Is the future actuarial profession smaller/larger than it is today? In either case, how does it differ from today in terms of make-up, deployment, function, purpose, value add, etc.?

Description: Creating a predictive model is one thing, but then taking that model and getting full stakeholder buy-in is another. Learn from presenters' experiences and insights on proving model effectiveness in the long-term care (LTC), life and annuity spaces. Explore various topics such as feasibility, model transparency, fairness and equity, ROI measurement, data assets and compliance, infrastructure and more. By the end of the session, you will gain an understanding of how to navigate the challenges of proving the effectiveness of predictive modeling and obtaining management buy-in.

Description: In this session a panel of industry experts from the life insurance industry will examine the modeling challenges created by increased investment in more esoteric assets.

Description: How do we take a Minimum Viable Products (MVP) approach to launch new insurance products? Join this moderated discussion and focus on three key development aspects: Distribution, Systems, and the design and pricing of the Insurance product itself. Come discuss reasons to choose an MVP approach and how it solves many of the product launch challenges.

Description: Welcome to the future of insurance, for actuaries and non-actuaries! Discover how cutting-edge AI models are revolutionizing underwriting, risk assessment, and customer experience for the insurance industry. Experts in management consulting and actuarial consulting firms will provide valuable insights into the consideration and challenges surrounding the adoption of Generative AI.

Description: As insurers search for ways to optimize the value of their actuaries, cloud-based data architecture has emerged as a leading solution to deliver quality data that enables the unlocking of actuarial potential. Hear an introduction to cloud based data architecture, explore cloud-based data strategies and view a live demo. Learn about different data “zones”, piping data between the zones, transforming data, and a collection of cloud-based tools that could be used for each one of these steps.

Description: The frequent use and complexity of today's actuarial projection models has increased the importance of having efficient models. Model optimization can reduce both cloud costs and overall end-to-end clock times, thereby allowing companies to do more with less such as reducing close times, increasing controls, enhancing analysis, doing more complicated calculations, and/or improving employee workloads during the close. From design and data to execution and audit, come explore techniques that can be applied throughout the actuarial modeling process to optimize actuarial models for improved run-time, accuracy, and reliability. There will be a focus on techniques that don't rely on model compression. Topics covered include model design pitfalls, data handling, improving convergence on asset-liability projections, strategies for interacting with the cloud, and other tips for optimizing actuarial models.

Description: Zero-Knowledge Proofs (ZKPs) represent an innovative suite of cryptographic algorithms that empower the insurance community to validate the accuracy of sensitive information without revealing the actual information itself. Mutation with the use of non-traditional data entering the insurance processes of customer acquisition and in-force management is currently taking place. A shift toward using non-traditional data in insurance customer acquisition and in-force management processes is currently taking place. This evolution is captured in the Australian market through surveys and interviews. Come and join us to learn about these two new research studies that open up the possibilities for the insurance industry to be more efficient in delivering its value to the society.

Description: Dive into this review on Artificial Intelligence and Machine Learning (AIML) techniques for actuarial modeling for life & annuities. Presenters will showcase learnings from the recent SOA research paper "Predictive Analytics and Machine Learning – Practical Applications for Actuarial Modeling" (Nested Stochastic). The researchers will go over models and methodologies used to develop high-fidelity proxy models for various life & annuity applications.

Description: Generative artificial intelligence (AI) tools like ChatGPT will redefine the nature of work across industries in coming years, What does this mean for the actuarial profession? Delivering generative AI tools to actuaries capable of leveraging them effectively will dramatically modernize how actuaries work and contribute to organizational growth. In this educational session, explore how generative AI can accelerate actuarial model development. Gain an introduction to generative AI and its implications for actuarial modeling. Learn how it specifically helps actuaries improve accuracy, reduce errors and save time in model development. Then explore use cases, including how generative AI can improve data cleaning, model building, as well as simulate scenarios and test model robustness. Close with a discussion on how to integrate generative AI into actuarial modeling workflows effectively, including common challenges actuaries may face during implementation and tips to overcome them. You will come away with a deeper understanding of how generative AI can accelerate actuarial model development.