In this paper we develop Quasi-Monte Carlo techniques for the evaluation of high-dimensional integrals that occur in financial applications, namely in the pricing of default-risky catastrophe-linked bonds in a model including stochastic interest rates, basis risk and default risk. It is shown that these techniques clearly outperform classical Monte Carlo integration in terms of efficiency. The methods are based on number-theoretic low-discrepancy sequences such as Halton, Sobol and Faure sequences.