Description: Learn from panelists from different companies as they come together to discuss their experiences.

Description: The topics of ESG (Environmental, Social & Corporate Governance) and sustainability are an increasing area of focus for insurance companies, and thus actuaries. This webcast provides a primer on these topics along with considerations for US valuation actuaries and their evolution in European insurance markets.

Description: Learn how modernization of data, models, and technology are influencing workflows. This webcast will address how workflows are changing in response to new regulatory requirements and the impacts the changes have on modeling and end-to-end future state operating models. Industry leading actuaries will discuss: How team collaboration can increase quality and speed of reporting to internal and external stakeholders How to strengthen controls and compliance frameworks across finance and actuarial departments How to modernize actuarial input/output for strategic analysis and insights How to attract and retain top talent by improving opportunities for actuaries There will also be dedicated time to ask questions of those who have made the transition.

Description: This session will showcase how from an actuarial perspective IFRS17 has its roots in market consistent valuations. It will also show how International Financial Reporting Standard (IFRS) 17 is rooted in probability-weighted stochastic scenarios-same as fair valuation, and how initial recognition sets the stage, as in the pricing basis and report, for actual experience to emerge as in the subsequent recognition. A detailed model will be given for a simple annual premium non-par endowment and actual numbers given and explained. The stochastic model will explain in detail the key reserve items in IFRS 17 including: - Liability for remaining coverage (LRC) - Risk Adjustment (RA) - Contractual Service Margin (CSM) And it will explain their interactions with one another. A discussion will be held regarding universal life policies with simple interest guarantees. And how these guarantees merit a valuation similar to Lookback options because of their path-dependent nature.

Description: Runtime of actuarial models and their associated processes has been a growing concern amongst the industry. This session will explore how expanding regulatory requirements, refined analytical objectives, and the desire for process optimization have increased the amount of processing power needed to get answers in a timely manner. Presenters will dive into how companies are leveraging data, refined pre- and post-processing routines, runtime reduction techniques, and cloud-based solutions to increase their efficiency in producing, analyzing, and validating model results.

Description: This session will discuss two important dimensions of why a holistic approach is recommended over a piecemeal, nonintegrated approach for an IFRS 17 modeling solution. Attendees will receive three perspectives from actuaries working as actuarial consultants or within an insurance company or as a software developer. The first dimension is model design. The session will demonstrate holistic model design advantages with regards to model inputs, model outputs, liability portfolio management, modeling efficiency, and transparency. The second dimension represents organizational impacts resulting from the model design.

Description: The NAIC is in the middle of their GOES (generator of economic scenarios) project to change the real-world economic scenario generator (ESG) prescribed for principle-based reserve and capital calculations.

Description: Asset liability management is an important task for any insurer, where tools like Excel play an important role from an analytics perspective. Dashboard tools like Power Bi and Tableau can supercharge an organization’s ability to perform ALM with real-time precision and monitoring of risk/imbalances. The dashboard can provide insights into potential risks posed by asset allocation and concentration, allowing for informed decision-making to mitigate those risks. The presenters will walk the audience through an example of ALM use case, including how to build key performance indicators such as cash flow, asset allocation, and risk exposure. Additionally, we will demonstrate how these types of dashboards can be customized to fit the specific needs of your organization.

Description: ALM and hedging can reap significant benefits from innovation in computation and operations research. Explore applications of static and dynamic optimization in two different ALM and hedging use cases. Insurers are increasingly moving offshore by establishing Bermuda captive reinsurers. In calculating the Bermuda Best Estimate Liability ('BEL'), reinsurers will need to segment assets to support liabilities in each treaty. A Linear Programming ('LP') problem can be formulated to tactically select assets in a way that minimizes the BEL and consequently the total asset requirement. Learn more about what US Variable Annuity Insurers face with the regulatory requirement to reflect 'future hedging strategy' in their statutory funding calculation. The traditional numerical method of finding the optimal hedging target and then allocating assets may encounter the curse of dimensionality with expanding product and economic environment complexity. A Reinforcement Learning algorithm may well fit this problem and provide insurers a solution for dynamic hedging.

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.