We are reaching a tipping point in which novel factors affecting human mortality and morbidity are outpacing the ability to predict their impact using traditional risk modeling. For centuries, humans have – for the most part – been getting sick and dying from well-known and well understood factors, such as heart disease, cancer, and accidents. However, for the first time in history, there are many likely millions of people alive today who will die from things yet to be realized. The insurance industry can only survive if it can effectively predict and price risk, but how can we keep pace with dramatic increases in risk variety and velocity when actuarial models rely on thousands of lives and decades of data? In this presentation, discover how insurance leaders could potentially leverage advances in quantum computing, applied artificial intelligence/machine learning, and in-silico medicine to rapidly ingest data, use new evidence types, and predict risk at paces never before attempted.