We've just released Wolfram Finance Platform with a simple aim: take all the experience we've built up in computation and as a development platform from other areas--whether biology, knowledge or rocket science---and apply it in finance.
It's amazing how little cross-pollination there is between computational areas. Each area has largely had systems with their own lingo and customs and only the types of computation with which they have become familiar.
We can do a simple demo of graph layout of stock correlation to a group of financial engineers and they are impressed. Well, we do have a very nice implementation, but the algorithms are well established and standard fitment in areas like social network analysis.
Finance is clearly an area where the analytics needs rebuilding, particularly for risk. In truth, it's a mixture between questionable analysis and antiquated reporting. So it's not just straight computation we're talking here either. It's high-level language, instant interactive reporting and linguistic interfaces to name a few. But what it really needs is the coherence of having an all-in-one system with intelligent automation that builds trust.
This is just the start of taking Mathematica technology and doing much deeper deployment in finance and other, different verticals.