Data controls have typically been assessed in terms of the risk to an individual institution without a broader consideration for the financial system. This, in turn, led to a divergence of institutional reporting practices and consistency of the data provided to the regulator.
In April 2009, the G20, in consultation with the International Monetary Fund (IMF) and the Financial Stability Board (FSB) established the Data Gap Initiative (DGI) as a response to this aspect of the crisis – a request to identify, and then address, the major financial and economic information gaps across the industry.
BCBS 239 is the foundation of this regulatory journey, laying out high standards for data quality, aggregation and reporting. Organisations will, however, have a major challenge in achieving the objectives of BCBS 239 through their existing fragmented architectures, disparate data structures and isolated control frameworks.
In response to this many firms will already be planning their next big data warehousing solution; a mechanism to extract data from isolated operational systems with a view to creating a unified central repository of all operational data. This paper argues that data warehousing is, in fact, a critically flawed proposition, particularly when applied to remediate data quality issues.
Fortunately, there is now an alternative. Data Virtualisation (DV) is a highly scalable approach to data integration that adds much-needed agility to the MI reporting functions.
The DV approach has become possible through the development of advanced middleware that precludes the need for data to be extracted, transformed and then loaded into a highly complex relational data structure that attempts to encompass the entirety of the business reporting requirements.
The reusable nature of the design components within the middleware means that reporting development costs and timescales are likely to be significantly reduced – which will be of great benefit to the business in meeting aggressive regulatory timescales.
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