Due to their business activities, banks are exposed to many different risk types. Aggregating various risk exposures into a comprehensive risk position is an important but currently unsolved task. This shortfall stems from conceptual problems in constructing an appropriate risk model and the computational burden of determining a loss distribution that includes all relevant risk types. Peter Grundke addresses both issues. On one hand, he extends a standard credit portfolio model by incorporating correlated interest rate and credit spread risk. The analysis shows that the economic capital needed as a buffer to absorb unexpected losses in a portfolio can be severely underestimated when relevant market risk factors are overlooked. On the other hand, computational aspects are discussed, particularly the problems that arise when using computational tools developed for standard applications.