The NHS Counter Fraud Service (NHS CFS) will use a new fraud detection system that uses neural networking developed by the business intelligence software company to predict where fraud is most likely to occur.

Neural networks are artificial systems capable of sophisticated, almost "intelligent" calculations, similar to the human brain.

Jim Gee, director of the NHS CFS told VNU News Centre the objective of the deal was to reduce fraud to an absolute minimum. 'We're looking to work with SAS to develop much more advanced software than has been traditionally available.'

The NHS CFS has already recovered almost £200m since it was set up in 1998 - the equivalent of three new hospitals, more than 12,000 heart transplants or 46,000 hip replacements.

Since 1999, pharmaceutical patient fraud has reduced from £117m to £69m, dental patient fraud is down 25% to £30m and optical patient fraud has reduced from £13m to £10m, according to NHS CFS estimates.

NHS CFS says fraud by NHS professionals has fallen by up to 30%, and the amount of money recovered has increased sevenfold over the last three years.

Recent cases include the chief executive of one NHS trust successfully prosecuted for £50,000 relating to mileage claims and a GP in the West Country prosecuted for £800,000. In that case, two motor boats were also recovered.

But despite huge achievements Gee admits there's still work to be done. 'We want to learn from every type of fraud and we want to target our fraud detection work more effectively. Our first objective is to get something to protect NHS resources.'

Gee said fraud detection systems could be of enormous benefit to other public sector bodies, including the police force, as well as organisations in the private sector. 'But at the moment there's enough work to be done in the NHS,' he said.

The NHS is the largest organisation in Europe with an annual budget of £70bn.

In a statement health minister Lord Hunt said: 'We aim to learn from every example of fraud so that we continuously improve our capacity to detect and stop it. We shall be using the most sophisticated technology to target those who would deprive the NHS of the resources it needs for patient care.'