Description: Global trends in both technology and regulation are causing U.S. insurers to reflect more deeply 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.

Description: Come discuss the benefits and challenges of collaboration between academic institutions and industry stakeholders in shaping actuarial education and research agendas. Register for this event now.

Description: Actuaries today have unique opportunities to analyze, understand and use data for strategic decision making. With nearly unlimited computing power and a broad spectrum of data sources at our fingertips, we are enabled to support our actuarial judgment with comprehensive findings backed up by deep data analyses.

Description: "As digitization and automation rapidly progress in today’s life and health industry, issues with misrepresentation during the insurance application process are also becoming a growing concern for insurers around the globe. A recent survey finds that misrepresentation in application forms costs the average insurance customer an estimated 5% to 10% in higher premiums. In order to reduce this risk, insurers must find and correct areas of misrepresentation, consult post-issue sampling, review the automated underwriting processes, and monitor the quality of financial advisory firms. Learn how predictive disclosure modeling detects and reduces misrepresentation by harnessing readily available underwriting data to analyze issues, helping insurers understand various drivers for disclosure rates and areas of misrepresentation.Advantages of this modeling to various stakeholders in the life insurance journey include improved risk selection, claims experience, and reinsurance terms for insurers. For customers, it leads to increased certainty of coverage, payout of the claim, and ultimately lower premiums on average. By the end of the session, attendees will understand: The disclosure modeling process at a high level The technical details of a standard approach to disclosure modeling: data cleaning, standardization, visualization, and predictive modeling Success stories about how predictive disclosure modeling has impacted insurers"

Description: How can generative artificial intelligence (AI) be leveraged to transform and modernize life insurance? Gain an overview of AI and some of their current use cases in the industry, including the latest trends in the market. Next, you will learn about the current challenges companies face, including costly underwriting procedures, customer acquisition and retention, and complicated application processes. Finally, explore how generative AI can help address these challenges, improve customer experience and help streamline processes to free up more time for higher-level business insights and other company initiatives.

Description: Get up to date on the current and potential use of artificial intelligence (AI) in the health care space. In this interactive session, you will learn how AI is being used today and discover its potential to reshape and revolutionize health care. Take advantage of the opportunity to find out how AI can influence patient experience in every phase of health care delivery, and join the conversation about the challenges and limitations that arise with the use of this technology.

Description: Catch up on conversations being had around the use of cloud computing. A panel consisting of a broad group of experienced actuaries on the front lines of implementing models within cloud environments will discuss the following topics: - Assumptions and calculation methods for optimizing runtimes - Strategies for reporting - Parallelization of calculations - Use of open systems to optimize runtimes - Organization of modeling teams to mitigate waste - Key machine specifications that impact runtime

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: Presenters will explore specific actuarial use cases, showcasing custom-built demonstrations and discussing a wider range of applications.

Description: The use of data to assess risk is not new to the life insurance industry, but has historically been limited to leveraging structured data. Join us as we discuss the next frontier: unstructured data.