Originating in the theory of uniform distribution, Quasi-Monte Carlo methods have become popular deterministic alternatives to classical Monte Carlo for high-dimensional numerical integration. In this talk we will discuss some attractive theoretical properties of Quasi-Monte Carlo integration, where the notion of the discrepancy of a sequence plays an important role. Moreover, advantages and limits of its implementation in practice are discussed and for some applications in mathematical finance, the performance of the method is illustrated.