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Story URL: http://www.silicon.com/financialservices/0,3800010322,39161291,00.htm

Finance company finds way though Basel II maze
Case study: Data quality project helps Marks & Spencer Money with compliance

By Steve Ranger

Published: Wednesday 09 August 2006

Marks & Spencer Money has completed a data quality project that has helped it comply with Basel II regulations well ahead of the January 2007 deadline.

The company - part of HSBC - offers financial products including the credit cards and insurance policies.

As well as complying with the Basel II Capital Accord - which requires the tracking and reporting of ongoing exposure to credit, market and operational risks - M&S Money wanted to improve customer data accuracy which would then improve the quality of business intelligence data.

Neil Hershaw, information management officer at M&S Money, explained: "Basel II was the final piece in the jigsaw when looking to justify a data quality project. For Basel II compliance we had to put a lot of effort into processes people and technology."

The increasing amount of customer data stored had made the quality of that data more of an issue, he told silicon.com. "Fifteen years ago people didn't have much data about customers and it was in their operational systems. Now we've got many terabytes of information in huge data warehouses. But if that data is wrong it doesn't matter how good your model is, the results will be skewed."

M&S Money chose Informatica's PowerCenter data integration package, using the Data Quality and Data Profiler modules to check the quality of data going into and coming out of its Oracle datawarehouse to make sure the business intelligence data remained accurate.

The same packages were used to assure the sustained accuracy of data derived from third party feeds, such as those from insurance policy providers.

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The project began with defining data quality rules for the relevant files and tables, then coding those rules, running the data, then analysing the data and creating a plan for improving quality assurance.

Hershaw said there isn't a one-time fix for data quality - levels are checked formally on a quarterly basis.

He said: "Data quality is a cumulative thing. It's not a project - data quality is an ongoing thing you have to have in every organisation. People have to see it as something they have embedded in the organisation."

And it's not all a technology problem, he pointed out: "It's not always an IT fix it might be a training fix or a process fix - it doesn't have to be rocket science to fix some of these issues."

Ovum analyst Ian Charlesworth said data quality is an issue many companies are looking to address, and are using regulatory compliance projects as a hook to hang such programmes on.

He said: "What's happening is those hooks are becoming more easily identifiable - whether it's a compliance project - it's becoming easier to explain to the business why data quality is important."