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.

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: 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: 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: Hop into a panel discussion between InsurTech Advisory Council and a startup, followed by a demo of life event prediction and analyses with multiple applications across financial services. You will also learn about: the SOA office hours program and member participation, the startup ecosystem filled with incubators, company contests, opportunities and outcomes, how to build a data set providing additional insights for customization and enhanced user experience, and - actuaries' engagement with startup strategic advisory boards.

Description: What is bias? How do you recognize it? What to do if you see it? This webcast will help respond to these questions and provide initial guidance on how to deal with these thorny issues. Please join us with your questions and we will have a nice conversation.

Description: Summary of an expert roundtable on generative AI in healthcare and health insurance, focusing on use cases, governance, trust, risks, and evolving actuarial skills.

Description: The global doubling of information content has been estimated to occur at a rate of every 12 hours, and conceivably faster. This ‘infowhelm’ is a double-edged sword for insurers. While maximization of the global knowledge base can fuel innovation, it can occur only in the context of reasonable cost for a higher benefit. The insurance industry – underwriters and actuaries in particular – are challenged to constantly examine new innovations that promise to raise confidence and protective value for insurability, within legal limits. This report aims to be the first of several to alert the SOA of promising innovations for the profession.

Description: The objective of this paper is to provide a practical guide with concrete case studies to help actuaries implement artificial intelligence and machine learning (AIML) to help accelerate the speed of analysis for life and annuity actuarial modeling. We do so by researching the existing literature regarding AIML and its applicability to stochastic modeling and exploring case studies.

Description: The rapid advancement of technology today will revolutionize how humans interact with their vehicles in the near future. Vehicle manufacturer initiatives to incorporate new technology into their products should usher in societal benefits such as improved driving safety, enhanced fuel efficiency and potentially lower costs for insurance.