The specification of dependence structures and the assessment of their effects on the total risk capital are still open issues in modeling operational risk. In this paper, we investigate the potential consequences of adopting the restrictive standard Basel loss distribution approach instead of strategies that take dependencies into account explicitly. Drawing on a real-world database, we fit alternative dependence structures, using parametric copulas and nonparametric tail-dependence coefficients, and discuss the implications on the estimation of the total risk capital. We find that risk-capital estimates may increase relative to those derived for the standard loss distribution approach when explicitly accounting for the presence of dependencies. The difference in the risk-capital estimates can be explained by the (fitted) characteristics of the data and the specific Monte Carlo setup in simulation-based risk-capital analysis.