A framework for generating Monte Carlo simulations for a portfolio of risk variables exhibiting interdependence is presented. The framework's structure is versatile, allowing the user to opt between dependence structure sophistication and computational efficiency. Consideration for underlying variable dependence is especially important for the quantification of extreme value statistics of financial and insurance portfolios. To build the methodology, copula theory, factor modeling techniques, and the Julia programming language are leveraged. The methodology iswidely applicable and agnostic to the underlying risk variable distributions. The presentation will explore how to incorporate both numerical and categorical factor inputs into the dependence modeling paradigm. Although there are many potential applications of dependency modeling and Monte Carlo simulation, the presentation will focus on the application to risk accumulation.