Monte Carlo is synonymous with fast cars, fast money and—in financial circles—a painfully slow way of valuing derivatives.

Now, banks are turning to machine learning in a bid to give their pricing models a turbo-boost.

The technique involves training so-called deep neural networks to approximate the results of Monte Carlo models without having to run millions of simulations.

“The neural network approximates the price of your portfolio when you’re running gigantic, complicated XVA calculations