Description: The frequent use and complexity of today's actuarial projection models have increased the importance of efficient models. Model optimization can reduce both cloud costs and overall end-to-end clock times. This, in turn, enables companies to do more with less, such as reducing close times, increasing controls, enhancing analysis, doing more complicated calculations, and/or improving employee workloads during the close. From design and data to execution and audit, join us to explore techniques that can be applied throughout the actuarial modeling process to optimize actuarial models for improved run-time, accuracy, and reliability. We will focus on techniques that don't rely on model compression.

Description: This session will delve into the valuable lessons learned from recent accounting change implementation, covering both model and process optimization. Attendees will gain industry knowledge as we explore optimization decisions made by others, highlighting both successful strategies and areas for improvement. We will discuss key decision points throughout the entire actuarial process, including data manipulation, actuarial calculation engine, and post-model reporting.

Description: This session will focus on the topic of Bermuda Reinsurance: Operational Readiness for Changes. The presenters will examine the current state of the reinsurance industry in Bermuda and explore the operational strategies that companies must consider to stay ahead in a rapidly evolving market. The discussion will cover regulatory updates, and market shifts that are influencing the way reinsurance businesses operate. The presenters will also discuss operational capabilities and organizational structure to think about when designing a new entity.

Description: Much of the work performed by disability insurance actuaries depends on the availability of accurate and detailed data, which is not always as simple as it sounds. Explore a variety of data challenges faced by disability actuaries, along with potential solutions. Potential topics include finding relevant data, the impact of poor data on valuation work, the impact of new privacy rules, and the potential bias in the data used to develop predictive models.