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The Evolution of Event Processing
CEP spending rises along with the technology's applications
January 22, 2008
Over the past year there has been a great deal of buzz about complex event processing (CEP), the system of harvesting events and correlating them for maximum organizational intelligence. Though the concept has long been associated with academic research, the financial markets have successfully addressed several issues with CEP methodology and are utilizing the programming framework in an increasingly effective way.
The capital markets are a natural place for a technology that is, fundamentally, based on the idea of processing data and relating it in a logical, temporal and ultra-fast way. Many of the first-generation CEP solutions centered on algorithmic and strategy trading, but the technology's applications are moving far beyond that.
A variety of problems become much more manageable when restated with an event processing formulation; complicated coding endeavors can be greatly simplified.
Algorithmic execution, strategy trading, liquidity sourcing, and routing engines provide the testing ground for many event processing tools. The algorithmic space, for example, is still rapidly evolving. Creating algorithms that look at individual stocks in a particular way, or provide more effective options trading strategies, will require the rapid incorporation of more complex data-utilizing technologies.
The current data explosion, and the need to use that data in increasingly diverse ways, has created a wealth of opportunities for CEP. The influx of data into financial firms poses many challenges, from getting information into systems in a timely fashion, to comparing it to data from five seconds or five years ago, to storing what is necessary. Perhaps most important, though, is a firm's ability to use correlation, comparison and pattern recognition to maximize the potential intelligence from the data that feeds almost all of its processes--trading, risk, compliance, collateral movements and reconciliation, among others.
CEP's continued growth will stem from the application of an event-driven architectural framework to larger-scale projects, as well as extending the technology to new areas. For example, business intelligence (BI) tools capture, analyze and interpret large stores of data, but building such tools on top of a CEP engine yields real-time BI. Likewise, business activity monitoring (BAM) becomes much more intelligent with event processing.
CEP technology providers are making event processing systems broadly available, and the growing demand for such applications could lead to a much greater CEP footprint in just a few short years.
While many firms have implemented custom-coded or in-house CEP projects, more and more vendors are bringing solutions to market. These products promise to deliver speed and throughput, and can reduce development cycles, minimize the need for the highest-caliber, most expensive C++ and Java programmers, and reduce maintenance costs.
The majority of CEP solutions being purchased by financial institutions focus on data and algorithmic trading. But specialized trading firms are utilizing event processing architecture to create rapid trade-routing and liquidity-seeking tools, and some vendors are concentrating their efforts on the messaging middleware or caching space, creating event-based middleware. Others are creating products that focus on the intersection of event processing and BAM, or CEP and business intelligence, offering considerable value to the visualization of front-, middle- and back-office functions.
Major software companies' interest in the field is growing, with several of the largest global providers announcing CEP initiatives. Large global consulting firms, with sizable footprints in financial services, are using CEP to create highly innovative solutions.
