In the post-crisis era, financial institutions seem to be more aware of the risks posed by extreme events. Even though there are attempts to adapt methodologies drawing from the vast academic literature on the topic, there is also skepticism that fat-tailed models are needed. In this article, the authors address the common criticism and discuss three popular methods for extreme risk modeling based on full distribution modeling and extreme value theory.