Managing Data Quality: Completeness, Accuracy and Timeliness

Craig Taylor

In an intensive regulatory environment, it is quite easy to get into a bottom-up analysis of each requirement, pouring over the details and considering all possible hypothetical implications. However, the author’s experience is that the best approach to resolving an issue is to use a top-down, pragmatic perspective. Talking through a subject with practical examples usually leads to faster results. This chapter is written with that in mind, and also sets some foundations around expected standards and deliverables on data quality.

BCBS 239 requires many different aspects of governance and control, but key to all these requirements is achieving a sufficient level of data quality. This is easier to say than to achieve, especially for businesses with a past of mergers/acquisitions that have led to a range of component entities and legacy systems. For such a business, some might think this is an impossible target to achieve. Nonetheless, persistence is crucial and interim targets should be set to help move towards attaining quality data. The key thing to bear in mind is the setting of achievable targets.

The principles of the BCBS 239 regulation are designed to be high-level and non

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