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Quantitative Analytics in Banking: How do we get the Heads Out of the Sand

The press has got onto thinking about what is wrong with banking right now, it has taken a crisis to get them to focus. It has taken a crisis to bring the banks and their supervisors closer together, sharing a common objective and that at the very least is one good thing to evolve from this crisis. Supervisors and senior Bankers are at least on adjacent pages. But that is only in terms of the regulatory and transparency requirements, the theory, the jurisprudence if you will. It will take the G20 in April in London to actually set this in stone.

The question is how to get the banks to execute on this theory and build the solution (architecture) which seems to be a no-brainer.

In my view and if you look at the Obama administration getting behind Open Source and High Performance computing then you can see indications of the Solution Design to solve the banking crisis to which the new regulatory and supervisory framework will be oriented.

http://insidehpc.com/2009/01/20/house-democrats-have-innovation-on-...
http://news.bbc.co.uk/1/hi/technology/7841486.stm/

But since the time of the analysis by Marx on the industrial revolution, middle management has always been the problem, you could argue that was the point Time magazine missed this week, having put the great economic thinker and father of the alternative we face on its cover for the first time this week.

How do us quants get middle management's head out of the spreadsheet sand? How do we encourage senior executives in the software mega vendors who have the ear of the C-levels to actually execute upon the solution architecture which will bring a floor to this downward spiral wrecking our democratic system, the press in their role as protectors of freedom will support us now, they are ready to listen, we have to articulate the solution. The mathematicians are going to take over the bank, all this spin blaming mathematics for the credit crisis is just spin from middle management who never understood it anyway, protecting their reputations, it was their failure to put quantitative analytics at the top of the systems and thinking agenda which caused this crises and which is stretching it out longer than is necessary.

In my view it has to be about Open Source, almost certainly with a commercial backing in terms of support which solves the analytic and transparency bit. Open Source is not only exclusively about Predictive Analytics, it’s just that the Community aspect is eminently applicable to predictive analytics, since the problems are generally hard and are generally iteratively solved. There is no question that in general black box proprietary closed source predictive analytics has failed the banking industry and thus society absolutely and completely, lets face it.

On the other hand the large scale data management platforms for banking from IBM and SAP cannot in my view be bettered, they have invested so much intellectual capital in these platforms it would take millennia for Open Source to catch up in that layer of the stack but at the top layer it is commercialized Open Source, allowing the community and forge to iteratively investigate and refine the quantitative analytics we need to understand our highly complex world which is the answer to the current predicament.

We are systemically dependent upon innovations in financial technology now. Computation of risk capital in an holistic and comprehensive manner is the key to recovery from this crisis episode. We have to meet the complexity of our financial technology needs with our response in terms of technology technology and in this regard can I refer to you the following possible specific considerations.

http://www.union-legend.com/index.php?page=references
http://www.revolution-computing.com/industry/finance.php

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Tags: IBM, Open Source Predictive Analytics, REvolution Computing, SAP, Union Legend

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