Description: After more than a decade of a prolonged low interest rate environment, long-term Treasury rates have started to increase with higher volatility. While it is generally agreed that a modest increase in interest rates and inflation is beneficial to the life insurance industry, interest rate risk remains a significant challenge for life insurance industry to manage its long duration liabilities, especially under volatile interest rate environments. Learn how to proactively manage interest rate risk and improve capital efficiency through the cash flow based strategic asset allocation (SAA) framework. Discover practical examples of how to combine asset allocation with derivatives to manage tail risk and liability convexity.

Description: With seemingly unending demands on life & annuity companies for more intense and complex calculations, as well as greater sophistication around analytics, and all of this done at speed, never before has it been so important to seek out maximum efficiency in constructing models. In this session the panelists examine how the combination of various model efficiency approaches, pulling in many different facets of modeling and making it flexible enough to dial up or down various modeling components, can bring about incredible results. Not only does it become possible to produce and expand upon financial risk metrics via a building block approach, but also enables life insurers to produce analytics and dashboards to support strategic decisions that were simply not possible or cost effectively viable before.

Description: Best practices for a successful model conversion or transformation. It details the key stakeholders involved and the processes and tasks across various stages of the model conversion.

Description: Historical and actuarial perspectives on the coronavirus events of 2020.

Description: Recent research from Financial Finesse introduces a viable way to forecast the potential return on investment (ROI) of workplace financial wellness programs.

Description: The session will feature case study discussion of how insurers can improve their model architecture and data visualization to prepare for the increasing demands of the future. Actuarial data and analysis has long been limited by the complexity and diversity of historical systems. External pressure on insurers is higher than ever before, as new requirements take effect under PBR, GAAP Targeted Improvements, and IFRS17.

Description: Discussion of the diversification activities of a number of life insurance companies. This includes the formation of, or acquisition of, property and casualty insurers, variable annuity companies, mutual fund management companies, banks, finance companies, leasing companies, real estate development companies, televisions and radio stations, newspapers, software consultants and other corporate enterprises. Discussion includes: 1. Activities really compatible with the llfe insurance product. 2. Activities otherwise compatible with corporate objectives or offering potentially large profit centers. 3. Activities which can be an excessive drain on corporate earnings and executive manpower 4. The actuary's role in these diversification activities. Then the discussion goes into a discussion of corporate planning models

Description: Learn more about the predictive modeling that was applied to industry data for the lapse and mortality experience in the post-level term period. Novel approaches were taken to model the shock lapse, subsequent lapse, and mortality experience. Observe a demonstration of the Tableau tool, which was built to allow users to analyze data on their own.

Description: Recent research from Financial Finesse introduces a viable way to forecast the potential return on investment (ROI) of workplace financial wellness programs.

Description: This article is the first installment of a three-part series that aims to provide an overview of ESGs and will focus on the general motivation for stochastic modeling, its advantages and its limitations. Future articles will further break down the key factors of ESGs and the application of these factors to better understand the Academy Interest Rate Generator (AIRG).