  We introduce a new method to calculate the credit exposure of European and
path-dependent options. The proposed method is able to calculate accurate
expected exposure and potential future exposure profiles under the risk-neutral
and the real-world measure. Key advantage of is that it delivers an accuracy
comparable to a full re-evaluation and at the same time it is faster than a
regression-based method. Core of the approach is solving a dynamic programming
problem by function approximation. This yields a closed form approximation
along the paths together with the option's delta and gamma. The simple
structure allows for highly efficient evaluation of the exposures, even for a
large number of simulated paths. The approach is flexible in the model choice,
payoff profiles and asset classes. We validate the accuracy of the method
numerically for three different equity products and a Bermudan interest rate
swaption. Benchmarking against the popular least-squares Monte Carlo approach
shows that our method is able to deliver a higher accuracy in a faster runtime.
