Description: Attend if you are an organization interested in utilizing various kinds of client data to improve the whole insurance sales process, and to develop new applications. Interested parties may include distribution sales force, underwriting, claims, actuarial and finance departments within a typical insurance company, online distribution partners, health care providers and other consulting service providers. The research looks into various use cases, which are typically main issues in modeling in the insurance industry. The research also helps benchmark performance using different languages that may serve as a good reference when best to use a certain language to enhance the development cycle.

Description: Become informed about the approach and adverse effects of the regulation of third parties and advance consent by the proposed NAIC Consumer Privacy Protection Model Law #674. You will hear an explanation of the regulation of third parties through their contracts with insurers. Learn specifics on the negative effect on companies contracting with third parties. Find out more about the requirement for advance consent for use of personal data for actuarial and marketing studies, and hear two potential solutions .At the conclusion of this session, you should be able to explain concerns about contracting with third parties for external data under the Model Law and learn potential solutions to using personal data for actuarial and marketing studies.

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: Discuss issues related to illustrations, including illustration testing, ASOP 24, the illustration model regulation and AG 49 at the practice level. Come prepared with questions and comments on the world of illustrations and illustration testing. Explore ideas for what's working and not working in the illustration world and formulate plans to tackle pressing illustrations issues. At the end of this workshop, you will be able to Identify issues related to illustrations and illustration testing for life products, discuss possible ways to resolve issues issue identified, and explore the future state of illustrations and illustration testing for various products.

Description: As our industry rapidly adopts more advanced technologies, today's actuaries have more data and greater analytical capabilities than ever before. Nevertheless, these advancements come with their own set of challenges.Come explore the tools and techniques to optimize your processes and avoid common pitfalls so that you can get the most out of your experience studies.

Description: The InsurTech industry continues vibrant activity. Some areas of focus include transformation of the underwriting process, new data sources being used, focus on the consumer, automation and more. By attending this session, you will hear about some of the latest trends in InsurTech that are impacting the life insurance industry.

Description: Examine how investment portfolios have been changing over recent years with a panel of industry experts from the life insurance industry, and learn what lies ahead. This will be a highly practical session, with real-life case studies referenced as much as possible.

Description: Come hear about the latest trends and insights as this panel discusses the happenings in life insurance marketplace. The panel plans to cover product, regulatory, underwriting, marketing, and other trends to help keep the audience up to date on many of Life's changing events.

Description: Modeling Approaches and Challenges focuses on approaches to real world simulation and the challenges and considerations in real world simulation. Topics include: A frequency domain approach to build realistic multi-horizon scenarios. (Ortec approach) Cascade models structure linking models for major asset classes and economic variables. (Moody’s approach) Overview of models, calibrations & approaches within the context of different use cases. Deterministic & stochastic approaches. Importance of model re-calibration flexibility. We will also discuss specific insights into considerations and challenges in real world simulation, which include topics like: Setting capital market assumptions and/or calibration targets. Assumptions about correlation and causality. Calibrating the model to capital markets assumptions. Validating the model against capital market assumptions. Role of history, market data and stylized facts. Importance of back testing. Calibrating the model to multiple investment horizons. Inclusion of alterative asset classes such as private equity, infrastructure, and direct real estate. Associated issues of limited data, illiquidity and greater uncertainty about calibration targets.

Description: At the conclusion of the first part, attendees will be able to describe sources of reserve redundancy for products under Principle Based Reserve (PBR) and products under Commissioners' Annuity Reserve Valuation Method (CARVM). Such products include Term Life, Whole Life, Universal Life, and Fixed Annuity with and without rider. We will also review sources of capital redundancy from the C-1 factor under Risk-Based Capital (RBC) and assets such as Unrated Asset Credit Fund can have high C-1 factor even if its risks are limited. At the conclusion of the second part, the attendees will learn about potential Reserve Relief reinsurance solutions. Such solutions can provide Reserve Relief for annuity and term life businesses, as well as potential innovative asset-side solutions. Asset managers can structure assets that the C-1 factor aligned with the corresponding risk.