Silo but deadly?

The title of an article in The Economist (subtitle: messy IT systems are neglecting aspects of the financial crisis) suggests that many banks have huge problems with data quality and the fragmented IT landscape made it exceedingly difficult to track a bank’s overall risk exposure before and during the crisis. But also concluding answering such questions as ‘What is my exposure to this counterparty?’ should take minutes. But it often took hours, if not days.

The core question in difficult times: shall we emphasize on the technological support of our core business, or optimize the work flows? People often think, there is a trade off between supporting quickly emerging business ideas (in finance: new deal types, tradig strategies, ..) or the organisational aspects (including risk management).

It is assumed that mapping the quickly-emerging lead to quick-and-dirty prototyping that leads to quick-and-dirty sub systems.

But THERE ARE evolutionary prototyping platforms.

The compute-develop-deploy paradigm of Mathematica is a leading example, for all developments in quantitative fields, from the user-programmed desk top application to the largest scale enterprize-wide risk management system. With its link technologies Mathematica can integrate even legacy-system fragments, and its data base link allows for high data quality and consistency. Intelligent data aggregation and scalable built-in high-performance-computing enables in-time-decision support.

Again, it is not OR, it is AND.