Clean-up operation

At financial services company M&S Money, part of global banking giant HSBC, the pressure was on to meet the requirements of the Basel II accord – but also to improve the general quality of the data it holds on its customers.

By Neil Hershaw

Headquartered in Chester in England, M&S Money is a major UK financial services company. While closely associated with retail group Marks & Spencer, with which it works on customer-facing and marketing activities, it is in fact a wholly owned subsidiary of global banking giant HSBC.

Like all financial services providers, M&S Money faced the challenge of readying its information environment to comply with the Basel II Capital Accord by 1 January 2007.

In doing so, we wished to accomplish a number of operational benefits, namely: the assurance of customer data accuracy; a reduction of time taken to complete business analysis; and increased confidence in the quality of data from which business intelligence (BI) reports are created.

We therefore planned and implemented a data quality project to ensure compliance with Basel II (which necessitates the tracking and reporting of ongoing exposure to credit, market and operational risks), and introduced improved data-management practices across the company.

As a company, M&S Money offers a wide range of financial products, including the &More credit card, travel money and various insurance policies.

We needed to meet Basel II’s requirements in order to ensure that our credit-risk management practices met internationally-recognised levels of consistency and, therefore, enabled us to accurately measure our capital adequacy – the reserves of capital we are required to maintain. The challenge was set and the company had to step up to the mark!

Compliance and customers

When we started looking at the compliance issues, however, we felt that this would be a good opportunity to conduct a broader, more holistic review of our data management and data quality processes. We quickly realised that there were other potential benefits to be enjoyed.

These centred on the need to avoid potential customer frustration caused by inaccurate or inadequate data, enabling the company to undertake better business analysis and, therefore, to target sales and marketing activities with greater confidence. In essence, we wanted to ensure that customers experienced no ‘surprises’ when approached about new products and services.

Historically, Marks and Spencer has always had a reputation for delivering excellent customer service and, in order to maintain the reputation of the brand, we had to ensure that our customers were given the same exemplary level of service.

As such, if our teams are not completely confident about data accuracy, and therefore a customer’s likely interest in a product or service, they will not approach them at all, rather than risk any frustration. Therefore, enhancing data quality would, we felt, drive improved business analysis and sales practices and, ultimately, help to improve customer loyalty.

One specific area that needed to be monitored was mapping data inputted on our website. As customers enter their own data, we have limited control over what they enter in each field, meaning that when the information is added to the database, it frequently requires closer scrutiny.

The most common errors we have experienced historically are customers mis-spelling addresses and forgetting (or neglecting) to put in area codes for phone numbers. Using poorly entered data meant that our customer-service agents could not use correct information when they engaged with consumers – jeopardising the level of service we needed to deliver.

This is unacceptable in any organisation, but particularly critical in a business such as M&S Money that takes a pride in its customer service levels, and the data quality initiative that began with Basel II compliance quickly evolved to cover other such business disciplines.

Measuring and monitoring the quality of data means we avoid engaging in any activity where we believe the quality of data is not accurate until improvements can be made. The challenge when you encounter quality issues is to introduce change into your organisation quickly.

But at least if you know there are issues with the data before you take action, you can treat that data accordingly. When running analysis on data that is not quality-checked, you are taking a risk on the accuracy of that reporting.

Measuring the quality of that data and taking action where necessary reduces that ‘unknown’ factor, but can never eliminate it. The fact that data quality degrades over time means that the measurement of data needs to take place on a regular basis, otherwise you find yourself falling behind again.

The Basel II challenge M&S Money has grown significantly since it was founded in 1985 and has a long-standing reputation for the quality and reliability of its products.

Compliance with Basel II therefore represented a special challenge for us because the changes required to the information environment also had to provide a platform that could deliver consistently accurate data, day after day. Not only did the company need to achieve compliance for legislative reasons, but in doing so it wanted to embed a ‘data quality culture’ in which virtuous practices are reinforced and the risk of poor-quality data being entered into databases minimised.

The goal in that regard was to ensure that customer data could be used with complete confidence in all customer management scenarios, so that M&S Money customers were never at risk of perceiving that the company had engaged in ill-informed correspondence with them. To achieve optimum levels of data quality and therefore service, the first part of the process involved assessing the value of particular items or classes of data to the company.

Some data, especially address data, needs to be 100 per cent accurate and therefore we strive for that. Other items of data may be of poor quality, but if there is no benefit to the customer or company in improving that quality, then there is no point wasting time and money trying to improve it.

Basel II is a demanding piece of legislation that requires extensive expertise and sophisticated datamanagement capabilities if the quality and integrity of that data is to be consistently assured. We therefore needed to deliver a data quality initiative that ensured data was managed according to a set process or specification.

This specification was the result of a detailed piece of analysis in which all Basel II data items were documented and specific data quality rules assigned. This document was then agreed by all those involved before being implemented.

The solution M&S Money chose the Informatica PowerCenter data-integration software package as the cornerstone of the project, and Informatica Data Quality was deployed to analyse and assure the quality of data input and extraction from our Oracle data warehouse.

These products check the quality of data going into and coming out of our Oracle data warehouse according to pre-set rules to make sure the business intelligence data remains accurate. PowerCenter is a single, unified enterprise-data integration platform that enables organisations to access, discover and integrate data from virtually any business system, in any format, and distribute that data throughout the enterprise.

The other tool, Informatica Data Quality, provides data cleansing, data matching, and reporting and data-quality monitoring capabilities. It is used to design, manage, deploy and control individual and enterprise-wide data quality initiatives. By providing a complete platform for ongoing measurement, monitoring, tracking and data quality improvement at multiple points across the organisation, the tool enables business information ‘owners’ to implement and manage ongoing data quality processes – it is not a one-off project.

The process of designing and deploying this solution was a complex one. Given the impending Basel II deadline of 1 January 2007, M&S Money created a specification in mid-2004 for a data quality initiative that would meet the regulatory requirements and the Financial Services Authority (FSA) mandates, as well as delivering a platform for enhanced organisation-wide data quality management.

The initiative was driven by Paul Spencer, M&S Money’s financial controller, and Informatica was chosen because of PowerCenter’s technical attributes, its scope for customisation and its ability to integrate a multitude of disparate data feeds.

Our data warehouse takes more than 60 feeds from all our operational systems, such as the M&S Money website, on a regular basis, in order to create a single customer view. In total, the Informatica deployment took 14 months from planning through to final implementation.

Building such an all-encompassing infrastructure is a major undertaking and required outside professional services expertise. The Informatica team was a great help to us in this project, demonstrating a wealth of knowledge about how best to achieve the level of data quality required for Basel II compliance in particular, and brought the experience of managing similar scales of assignments for major banks and financial institutions.

But while there was obviously the need to satisfy the data quality elements of Basel II, M&S Money’s holistic approach to data management served to give the company a greater confidence in its activities in such areas as sales and marketing, contributing to a competitive advantage in the financial services market, too. The primary operational driver was that the company needed to be constantly ‘aware’ that its data was of the appropriate quality and that it could always demonstrate clear management of the data.

Informatica Data Quality was deployed as a data-quality management platform alongside the data warehouse to ensure that data feeds comply with the required quality levels – ensuring that BI data remains wholly accurate. Each data-quality project is set its own specific goals and objectives. These are also costed to demonstrate the value that can be added to the company.

Again, Informatica Data Quality provided the required support for these disparate data feeds and therefore enabled all data quality to be managed within a single framework. For example, feeds are received from our motor, home and contents, travel, pet and wedding insurance divisions and these are all particular to those products and their associated transactional systems.

The methodology for the project began with defining data-quality rules for the relevant files and tables, coding those rules, running the data, then analysing the data and creating an action plan for quality assurance. Having now completed the project, data quality levels are evaluated formally on a quarterly basis.

The results

The main driver for the business was compliance with Basel II’s stipulations, which was completed successfully a year ahead of the deadline. A further gain has been the reduction of the analysis cycle by up to 40 per cent, meaning faster comprehension and validation of information through less time needing to be spent assessing the accuracy of the data; that is to say, if analysts don’t have to spend the time up front analysing what’s in the file and the quality of the data it contains, then they can move straight on to delivering what they need to.

The IT department is now able to provide quantitative measurement of the data held by the organisation, which was a broader goal of the initiative. For a financial services company, that resource has proved to be invaluable.

Once the system went live, it took business analysts just four days to develop 20 Basel II business rules on the fly, deliver a data accuracy scorecard that is used by the IT team to ensure that information is valid, to create profiles on account history tables and develop other business rules that were then added to the scorecard.

In many ways, Basel II has been a blessing in disguise, as it spurred us to improve data quality across the organisation and the ability to measure that quality has improved our business in several other areas.

It is clear that business analysis has benefited, too, but there are also other benefits such as how we evaluate our sales and marketing activities. For example, we are now able to ascertain with confidence what activities have caused a sale, which is critical in developing our future strategies. The company lives by the mantra that customers must be presented with no surprises, but meeting the requirements of Basel II mercifully presented us with few surprises, too.

It was a tough assignment, but the detailed planning and execution we undertook enabled us to minimise the scale of the challenge. We are now even more confident that we will be able deliver on our commitments to customers and can assure high levels of data quality to assist in running our business.

Neil Hershaw is information managementofficer at M&S Money. He can be contacted via EI managing editor Graeme Burton, gburton@ark-group.com.