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: FASB published LTDI requirements in 2018. The effective date for insurers who are SEC filers to publish US GAAP financials under LDTI is January 1, 2023. The effective date for non-public insurers is January 1, 2025. LDTI requires insurers to identify a new category of benefits called market risk benefits (MRBs) in insurance products. Broadly, variable annuity (VA) and fixed indexed annuity (FIA) guaranteed minimum death, accumulation, withdrawal, and income benefits fall under MRBs. Valuing MRBs requires calculating the liability on a fair value basis. Valuing FIA MRBs on a fair value basis can be complicated as several aspects of FIAs such as option budgets and policyholder behavior are driven by company management decisions and the competitive landscape.

Description: The pension risk transfer (PRT) market has increasingly expanded to include the complexity of deferred participants who have additional options that do not exist for a retiree already receiving their benefit. Assumptions on the timing of benefit commencement and form of payment elected are highly dependent on specific pension plan provisions and the census population. These assumptions can have significant impact on the reserves and cash flows affecting not only the initial price but the future profitability of the deal and require a balance of both pension experience and annuity pricing. Learn about considerations for assumptions fit for purpose from pension actuaries working in the PRT market and who specialize in the assumption setting process for deferred lives.

Description: Operationalizing Generative AI for Actuaries

Description: The pension risk transfer market has increasingly expanded to include the complexity of deferred participants whom have additional optionality available to them that does not exist for a retiree already receiving their benefit. Assumptions on the timing of benefit commencement and form of payment elected are highly dependent on specific pension plan provisions and the census population. These assumptions can have significant impact on the reserves and cash flows affecting not only the initial price but the future profitability of the deal and require a balance of both pension experience and annuity pricing. Discover more about pension actuaries working in the PRT market and who specialize in the assumption setting process for deferred lives provide considerations for assumptions fit for purpose.

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: "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: There is a clear consumer need for long-term care (LTC) coverage. Combo life/LTC products sought to meet that need when stand-alone LTC coverages became more difficult and more expensive to get. Combo life/LTC are built to be more sustainable, allowing for more alignment of interests between the policyholder and insurer. However, combo life/LTC are typically on a universa life (UL) chassis with extensive secondary guarantees, and several were withdrawn from the market in the recent past because of very low interest rates. A couple of carriers have used the variable UL chassis which are still in market. Interest rates have also risen dramatically. The opportunity may be present for innovation in this area that leads to sustainable products. Join the conversation as experts in this area discuss the strengths, weaknesses, opportunities and threats in developing and marketing these products.

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: The document is about the post-wildfire drinking water crisis and its implications for the insurance industry. It discusses the contamination of drinking water systems by wildfires, remediation strategies, financial considerations for the insurance industry, and potential contributions from the actuarial community.