In this talk I will discuss the opportunity for innovative approaches to the use of models and data in the financial and insurance industries. The financial and insurance industries rely on stochastic models to manage the risk of uncertain future events in all their lines of business. While most of the effort focuses on developing the mathematical structure of the models, the lesser studied problem arises from the availability of data and the estimation of the models’ parameters. In fact, many financial theories assume that all the risk identifies with the stochastic nature of the model while disregarding the uncertainties of the models’ parameters. It turns out that parameters’ uncertainty, or the ‘risk of risk’, poses serious challenges for both theoretical and practical industry applications. I will illustrate the problem with some simple examples and discuss speculative ideas for more data-aware modeling approaches.