The explosion of strategies such as algorithmic trading coupled with regulatory compliance and increasingly complex financial engineering tools is leading to massive volumes of data within financial services organizations. Additionally, the notion of real-time is constantly being redefined by financial markets as brokerage firms march towards millisecond and microsecond trading in a frenzied environment that has witnessed significant activity despite a prolonged bear market.

As the volumes of data have swelled, so have institutions’ reliance on information. CIOs are now in a rather unenviable position as they operate on shoestring budgets, while attempting to convert an IT organization’s image as a cost-center to that of a competitive advantage. It is becoming evident that existing data infrastructures cannot scale to today’s data volumes. To cope with this data deluge, most organizations are making significant investments in data infrastructure technologies. Not surprisingly, a 2004 report from Financial Insights indicated that by 2009, roughly 28% of IT spending in financial institutions would be dedicated to data architectures.

Data-driven Front, Middle and Back Offices: The Promise

As opposed to most technological drivers in the enterprise, data accessibility and architecture improvements can have a positive impact on all functional groups - the front office, middle office and the back office – although for vastly different reasons.

Front Office – Profitability: It is as clear as daylight that the primary goal in the capital markets business is to increase revenues and profits, especially in trading operations. However, factors such as decimalization, increased competition and rapid adoption of electronic trading have stymied financial growth for such companies. Low-latency data networks can help fight these forces by enabling trade executions at profitable prices and by supporting higher trade volumes, leading to greater revenues especially in scenarios like program trading.

A robust data infrastructure can also guarantee non-stop operational environments and avoid downtimes and the associated monetary loss. In derivative markets that involves complex instruments spanning multiple asset categories. A nimble market data distribution mechanism can become extremely critical to assimilating information from multiple exchanges. Effective trading strategies can also be crafted using a new class of data management tools that can mine special patterns such as price movements in real-time from multiple market data streams.