Financial services data management: time to standardize

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87% of our survey’s respondents said they envisaged significant benefits in having a standardized approach to data management.

Who puts all their eggs in one basket? Very few of us. Major financial services organizations are a case in point. They’re competitive bodies, and to ensure the data services they use are of best-of-breed and suitable for their own specific needs they employ offerings from several different commercial vendors.

But upsides often have downsides, and in this case the problem is a lack of homogeneity. A survey recently conducted by A-Team Group for Capgemini found senior-level data management executives at financial institutions across North America and Europe complain that each vendor’s service is effectively bespoke and that consequently they are obliged to adopt the standards – data definitions, identifiers, data models and more – used by each of their suppliers.

Respondents said the lack of standards and of collaboration among providers mean process standardization is impossible. As a result, they said, they are obliged to allocate significant sums to integrate disparate data sources, even where coverage is essentially the same. The survey found this effort is duplicated across the industry as organizations attempt to integrate the same data sources to address the same internal data integration needs.

In short, it’s cumbersome, costly and time-consuming, and it dilutes the benefits accrued from each of those best-of-breed offerings. So it’s small wonder that 87% of the survey’s respondents said they envisaged significant benefits in having a standardized approach to data management. Such an approach, they said, would result in improved data quality, leading in turn to cost reductions from streamlined operational processes and reduced exceptions and reconciliations.

Standardization would also improve data lineage, which is emerging as the new ‘must-have’ for regulatory reporting; it would streamline new product implementations; and it would allow them to gain more control over data attributes. Finally, the survey respondents said they expected to see major improvements in data cleansing and validation, data sourcing and distribution, and management of identifiers and classifications.

Planning a route

But of course, it’s one thing to picture the benefits of a destination, and another thing altogether to chart a path to it. Our view at Capgemini is that it may be some years before we see any real industry-wide change.

In the meantime, organizations are going to need to tackle the issue on their own. Obstacles will include internal organizational and political issues in the form of business and data silos and legacy technologies. To overcome them they are each going to have to adopt a sequential approach, requesting the development of standard feeds from each of their providers in turn and bringing them together in a holistic model. There are no shortcuts, and to make it possible they’ll need to assign responsibility and a budget.

The goal is uniformity, and it’s a task with which seasoned global service providers can help. They have broad experience; they have a fund of knowledge of the prevailing standards; they can apply best-practice approaches from implementations in other sectors and geographies; and they can develop function-rich models that are fit for purpose in each organization’s specific circumstances. At Capgemini, we’re already working with CTOs at banks and other finance houses to help bring about the change that is so clearly needed.

Please click here to read the full report.

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