Description: The article provides a high-level, non-technical, introduction to artificial neural networks (ANNs) and deep learning with an application to risk management. The method relies on typical ANN components such as nodes, activation functions, and optimization through gradient descent.

Description: The mismatch between how interest rate impacts the value of assets and liabilities could have material negative impact to companies’ earnings and surplus. To quantify and mitigate the impact of such mismatches, companies have used matching a combination of duration and convexity. I will review these measurement techniques and their limitations.

Description: Strategic Risk Management was given lower priority in a recent survey of ERM Objectives. This article tells how the author believes that recent events have caused many to shift to a more short term focus and in the future there will be a shift back to a priority for the longer term view that stands behind Strategic Risk Management when the environment settles down and things again seem to be more predictable.

Description: Discussion of how to mature value-based contracts between health insurers and provider organizations to improve population health and financial sustainability. Centers around contract parameter consistency, revenue predictability and risk assessment. Intended audience are health plan and ACO actuaries and leaders. Authors are writing from the provider perspective in value-based contracts.

Description: Back in the day, when data was scarce and computers were slow, actuaries were forced to use simple methods to account for risk. By far, the most common method was to add a margin, usually 5% to a “best estimate” calculation. Remarkedly, this method still works quite well in the aggregate. The problem is that, in many cases, decisions today require a more in-depth analysis. For example, how big a risk is a health plan really taking if it lowers its premiums by 10% to attract more members? This session will discuss techniques for measuring risk in today’s environment. Speakers will also share the results from the 5/50 research project, which forms the foundation for the techniques.

Description: This research report that provides a literature survey of methodologies applying machine learning to insurance claim modeling.

Description: This article is part of a 2 part series on real options analysis (ROA). Before you can understand the limitations of ROA, you must first understand the difference between risk and uncertainty. This article goes into detail explaining the vast differences between the two phenomena.

Description: Essays advocating for incentive compensation linked to the level of risk in an organization.

Description: This research report models the impact on the U.S. insurance market resulting from a post-Brexit economy in the UK.

Description: After a very challenging year, actuaries need to look back and consider the lessons learned. Have we returned to where we were, or have we moved on to a new norm? What does the COVID-19 pandemic market data tell us that will help us to prepare for future global crises?