Neural Networks for Credit Risk and xVA in a Front Office Pricing Environment
We present a data-driven proof of concept model capable of reproducing expected counterparty credit exposures from market and trade data. The model has its greatest advantages in quick single-contract exposure evaluations that could be used in front office xVA solutions. The data was generated using short rates from the Hull-White One-Factor model. The best performance was obtained from a GRU neur
