Never in the history of banking has the need to have good quality data been as important as it is today. As the after effects of the 2007-2009 global financial crisis linger on, ever fewer funding sources and an increasing pressure on financial institutions to deliver a respectable return to their shareholders has increased reliance on high quality data.

Add to that the tough requirements from new regulation such as Basel III including the need to have more regular and precise data on risk exposure, and it becomes clear that data warehouse management techniques that worked a decade ago or virtually impractical for international banks today.

Matters are further compounded by the sovereign debt crisis especially in European Union countries such as Greek, Ireland, Italy, Portugal and Spain. The implosion of what were once thought of as near risk free investments has forced financial institutions to further interrogate their balance sheets and put in place more robust, comprehensive and anticipatory measures that can withstand sudden regional or global shocks.

There is no denying that the financial markets environment has radically changed over the past few decades. In the 70s, 80s and 90s, new regulations were few and far between. Today, it is not just the compliance demands of new regulations such as Basel III that are exerting strenuous demands on data among global banks. Compliance with Basel III must be carried out in the context of the surging numbers of ad hoc, country/region specific requests e.g. the current stress tests on US banks conducted by the Federal Reserve. Discrepancies or other elements that cast doubt on the accuracy of data used to generate reports can draw greater attention from regulators and in the worst case, increase the likelihood of supervisor intervention.

Basel III sets new standards for data quality adding a completely new set of demands on a financial institution’s data warehouse. Banks must make optimize enterprise data to make it easier to comply with the new liquidity, funding or regulatory reporting.

Probably the best example of how the new Basel standard will exert even more pressure on the data warehouse and data management is the rules around counterparty credit risk and collateral management. International banks will require detailed and timely data in order to keep track of collateral concentration in specific asset classes and continuously assess if such collateral is enough to cover net stable funding ratios (NSFR) or liquidity coverage.

To do this, the treasury, risk and finance teams within the bank must cooperate and provide the support necessary to ensure the data used is sound and validated.

Short term solutions no longer feasible

For an international bank to have such high quality data available for reporting, reliance on short term fixes and workarounds is impractical. Tackling every new compliance requirement in isolation is difficult and, in the long term, expensive. Financial institutions that have realized the futility of workarounds have adopted forward-looking and broader data warehouse infrastructure and data management strategies that would be fundamental not just for Basel III compliance but also for the successive regulations that are certain to crop up in future.

Why banks opt for stop gap measures

It is however important to note that no bank starts off with the intention of stop gap, short term solutions. Several reasons drive financial institutions to settle for workarounds. Top on most lists would be cost considerations – at least in the short term. As opposed to setting up a project team and dedicating substantial resources towards assessing and overhauling the current data warehouse and data management framework vis a vis new regulations, it seems cheaper to task a couple of members of the IT team to develop ad hoc modules that will generate the report the regulator requires.

Another reason for stop gap solutions is the constant state of evolution of a comprehensive framework such as Basel III which is still in its early stages of implementation. After all, why pour in vast amounts of cash into complying with requirements that might change? Some banks therefore opt to concentrate on the bare-minimum must-have requirements and save the heavier investment for later when they expect that the Basel III pillars will have crystallized.

A third reason is the perception that the final date for full compliance, 2019, is very far off. This is especially apparent when you consider the many competing compliance and business interests that may seem more urgent. The bank ends up allocating a smaller budget and fewer personnel to Basel III compliance while channelling the bulk to more ‘immediate’ needs.

Long term view to data management is no longer an option

Despite their allure, short term solutions to compliance provide only temporary relief and are never sustainable. A comprehensive plan and the development of detailed Basel III metrics early on can deliver vital competitive advantages to a bank including firming up market confidence, reduced risk of sanction by regulators, efficient long term use of resources and the capacity to pursue opportunities less prepared rivals may be equipped to chase.

The complexity and scope of Basel III’s data management requirements is almost certain to test and unravel any stop gap, tactical solutions. International banks cannot postpone a comprehensive response to the new framework on the pretext of buying time before the 2019 deadline. As has been seen in similar regulation, actual implementation timelines are likely to be less driven by the need to beat the 2019 target and more likely to depend on pressure from already-compliant peers and the expectations from the market.

Remember, Basel III is not the only regulation international banks have to contend with. The fact that the operations of today’s largest banks are not only spread across multiple countries but also across different areas of business, means that Basel III is often just one of several new rules that global banks must comply with. In this respect, the Dodd Frank Act, IFRS, Solvency II, MIFID and UCITS are other financial regulations that come to mind.

What’s more, such different regulations may have overlapping requirements. Developing a data warehouse and data management workaround for each regulation is inefficient and could ultimately lead to substantial rework that is otherwise unnecessary.

Author's Bio: 

Graz Sweden AB provides financial services players with the most cost-effective way to access, manage, and analyze their data. Using the flexible data management platform HINC, Graz’s data warehouse infrastructure helps manage tens of thousands of investment portfolios for several institutions including 9 insurance companies, 120 banks and the largest fund manager in Scandinavia. For more information, visit