A block-structured model for the reconstruction of directed and weighted financial networks spanning multiple countries is developed. In a first step, link probability matrixes are derived via a fitness model that is calibrated to reproduce a desired density and reciprocity for each block (ie, country and cross-border submatrix). The resulting probability matrix allows for fast simulation through bivariate Bernoulli trials. In a second step, weights are allocated to a sampled adjacency matrix via an exponential random graph model (ERGM) that fulfills the desired row, column and block weights. This model is analytically tractable, calibrated only on scarce publicly available data and closely reconstructs known network characteristics of financial markets. In addition, an algorithm for the parameter estimation of the ERGM is presented. Further, calibrating our model to the European Union interbank market, we are able to assess the systemic risk within the European banking network by applying various contagion models.