1. A computer-implemented method for calculating pricing information of a financial instrument comprising a plurality of underlying financial instruments, the method comprising: calculating in a computer system, a default time vector for each of a plurality of default scenarios wherein each default time vector includes a measure of a likelihood of default for each of said plurality of underlying financial instruments; calculating in the computer system, one or more cash flows for a subset of said default scenarios; training in the computer system, a neural network with said subset of said default scenarios, wherein the calculated cash flows for the subset of default scenarios are used as output training vectors for the neural network and the calculated default time vectors for each default scenario within the subset of default scenarios are used as input training vectors for the neural network; and using said trained neural network in the computer system, to estimate one or more cash flows for a remaining number of said plurality of default scenarios.