In this paper, we study factor-based subordinated Lévy processes in their variance gamma (VG) and normal inverse Gaussian (NIG) specifications, and focus on their ability to price multivariate exotic derivatives. Both model specifications, calibrated to a data set of multivariate barrier reverse convertibles listed at the Swiss market, demonstrate good ability in capturing smile patterns and recovering empirical correlations. We show how the range of correlations spanned by each model is linked to the process marginal distributions. Our analysis finds that a trade-off exists between marginal and correlation fit. A sensitivity analysis is performed, showing how a product’s characteristics and a model’s features affect multibarrier reverse convertibles prices. Market and model prices are analyzed, and discrepancies are highlighted and explained.