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. Learn more about model design pitfalls, data handling, improving convergence on asset-liability projections, strategies for interacting with the cloud, and hear about other tips for optimizing actuarial models. By the end of this session, you will be aware of the roadblocks that can reduce model efficiency and understand various strategies for reducing bottlenecks and getting the most out of actuarial projection models. TRACK: Technology/Model Development/ Artificial Intelligence/Machine Learning