Description: The advent of emerging technologies such as blockchain, decentralized AI, and advanced privacy preserving techniques have created the possibility that billions of individuals may be able to maintain sovereignty and control of their own data. As data becomes increasingly valuable as the means of production for a variety of digital goods and services, this self-sovereignty of data may create a new economic framework of individualized data monetization. This session will explore the key factors, technologies and mega-trends in health and medicine aligning to drive this new economy and explore what the future may look like from a data valuation perspective as the current $120 billion secondary market for health data expands to include consented health and health-relevant data from more individuals, to the benefit of all individuals and the healthcare system as a whole.

Description: InsurTech continues to significantly influence the insurance industry even though there is an economic downturn. For insurtechs focused on profitability and efficiency, the landscape of opportunity looks more favorable. By attending this session, attendees will learn the current trends in InsurTech in a variety of lines of insurance.

Description: The landscape of the reinsurance industry is evolving amid profound changes in the insurance sector. Innovation is vital for reinsurers as risks become more complex and insurers transition from a role of "protection" to "prevention." Successful reinsurers are responding to market dynamics, particularly through open innovation – collaboration with startups.

Description: Every year an AI topic goes through a hype cycle. Since 2022 and now in 2023 we continue to hear more about the ChatGPT models and how an everyday person is able to interact with AI. As more startups and applications are riding the hype, what does it all mean for our industry? Is this just a buzz or real? This talk intends to cover at a high level what are large language models, what does it mean for audit or regulatory space, and what might be some pitfalls or tolerance of error when it comes to selecting a right application for such models in insurance use cases.

Description: Insurers are now in a better position than ever to both understand and enhance their customers' health and well-being. A key avenue for this is through developing health and wellness offerings for clients—for mutual benefit. Around the world, the proliferation of lifestyle and health data continues to gather pace.

Description: This session will explore the considerations and best practices for developing AI tools that are useful, safe, and transparent for actuarial work. While large language models (LLMs) offer exciting possibilities, it is crucial to understand when and how to use them effectively. The session will cover key concepts of LLMs and case studies on developing AI tools for retrieval-augmented generation and summary creation of actuarial documents. Attendees will learn about the importance of designing workflows that nudge users towards safe and effective processes. By the end of the session, participants will gain insights into the responsible use of LLMs in actuarial practice and learn how to leverage their potential to support professional growth.

Description: Understanding how to effectively adopt AI is critical to staying competitive. This session will guide you through the five stages of AI adoption, with a deep dive into two key stages: Operational Optimization and Collaborative AI Integration. You will learn how to harness AI to streamline operations and boost efficiency, while also exploring the nuances of integrating AI in decision-making to enhance outcomes through human-AI collaboration.If you are seeking practical insights on maximizing AI's benefits while maintaining human oversight, this session will provide the tools and strategies to help you do just that—ensuring that your AI adoption journey is both effective and aligned with your business goals.

Description: Blockchain and cryptography have seen significant adoption around the world. While still in early stages, it has started to make an impact in finance, gaming, and metaverses industries. Organizations have even began to provide insurance services on blockchain. Although insurance is limited to protection against financial losses in markets, the sheer adoption has sparked interest for other insurance use cases and some startups have already started experimenting in the space.

Description: Session 2– Going Deeper through examples InsurTech (1) identifies a pain point to the industry, (2) brings a technology solution to address the shortcoming with a (3) business model that makes sense for all. Expect an illustration of this three-point structure through a handful of start-ups from various backgrounds (health, life, general operation) dealing with various aspects of the insurance value chain (acquisition, risk management, back-office…).

Description: New digital data known as alternative data is everywhere. Our industry has seen the financial, and hi-tech industries leverage new digital data to expand their key offerings and core services. From the lens of the global life and health industry, new digital data is still searching to be further understood. Risk assessment is a current focus area for using alternative data. A key question is even though risk assessment has always been data-driven, can it now move to the next level with the arrival of this alternative data. Can we use alternative data to make the risk assessment process quicker, cheaper, or faster thereby driving more sales and better conversion rates. It is an exciting time! With the increased adoption of health and well-being apps, data such as physical activity, nutrition, sleep, and mental wellness is now readily available. Expanded data such as digital biomarkers, IoT data, electronic health records and many more can also be accessed. However, how to effectively implement alternative data remains a challenge across the industry. We firmly believe it is, and will continue to be, imperative to take a structured approach to alternative data through a set of key considerations and a framework of principles.