Today's business intelligence solutions require a whole new breed of mathematics and we asked André Zitzke, Solutions Specialist at of SAS to elaborate.

Q: Why has sophisticated predictive analytics, based on advanced mathematics, become an essential component of BI?

A:
The new rash of compliance legislation, for example the operational risk component of Basel II, has opened up a totally new field for mathematicians and statisticians. New maths is having to be developed to meet the demand.

Q: Corporates have in the past been quick to examine new mathematical concepts. What's different?

A:
Businesses have leapt ahead in their requirements, and the maths is having to catch up in order to solve new business problems quantitatively, as well as to cope with the vast volumes of data being generated today. In the past the question was always: Do we have enough data to do the analytics?" For example, large financial services organisations now have to analyse and predict their operational risk to comply with Basel II, a set of broad policy guidelines that each country's supervisors can use to determine the supervisory policies they apply. The new framework is intended to align capital adequacy assessment more closely with the key elements of banking risks, and to provide incentives for banks to enhance their risk measurement and management capabilities.

Operational risk is not a finite, tangible area that lends itself to traditional analysis. Instead, it involves a disparate mix of everything from business areas and functions to material loss events and physical security.

Q: How do enterprises face the challenge of investing in the right BI maths solution?

A:
SAS has a large numbers of PhDs - actuaries, statisticians and mathematicians - working in its research and development department. These experts either develop new maths themselves, or are well versed in the latest mathematical developments globally to ensure that SAS utilises these advancements to help businesses solve their current problems.

Q: Does this call for a new breed of employees?

A:
No, the good news is that need no knowledge of the sophisticated mathematics built into the solutions. There are basically two groups of users. The vast majority are in business or finance, and use the results of analysis to perform their functions. They use BI to look at specific scenarios, asking 'what if' questions such as 'if the interest rate changes, what impact will this have on the future financial state of the company, and what are the risks associated with it, and how can an organisation optimally hedge this risk?'

The other group are the quantitative analysts who understand the maths and stats behind the solutions, and develop statistically sound models that produce the results needed by the end users.