BGC Partners has come a long way with its business intelligence strategy since the company's inter-dealer fixed income electronic trading platform, eSpeed, was first launched in the late 1990s. Over the years, the New York-based company--which began as Cantor Fitzgerald and now provides integrated voice, electronic execution and other brokerage services to investment banks and traders--has increasingly focused on delivering customized, real-time data reports to its key decision-makers and customers to help them react more quickly to changing market dynamics and how that might be impacting the revenue mix across BGC's brokerage, settlement and other businesses.
Taking these efforts a step further, the company later this month is expected to implement Sybase's RAP - The Trading Edition system, a unified market intelligence platform that's designed to help BGC and other capital markets firms make more efficient use of data for analytics and reporting across the front- to back-office trade lifecycle. The system provides a single platform for access to common data shared by quantitative analysts, traders and risk managers, including support for real-time trade analytics and execution, pre- and post-trade risk analysis and intra-day regulatory reporting.
Chris Crosby, senior vice president and global head of corporate technology at BGC Partners, is hoping that the system will enable people in the company's finance organization to more quickly and effectively slice-and-dice trading and settlement data to determine how the company's brokerage, settlement and other operational revenues are allocated each day. In addition, managers in BGC's operations group should be better equipped to drill down on settlement data to help them determine the company's risk exposures on open trades and across the different products it sells, says Crosby.
BGC's increasing reliance upon BI for more on-the-fly decision making and intra-day risk monitoring and mitigation reflects the types of emphasis that securities firms have placed on analytical techniques since current market upheavals began roiling the industry last summer.
Indeed, securities firms today are increasingly utilizing business intelligence and analytics in three areas: risk modeling to determine value-at-risk, stress levels, and capital adequacy; quantitative analytics for modeling investment strategies; and analysis of high-frequency trading strategies, says Dushyant Shahrawat, senior research director for investment management at TowerGroup.

Mitigating Risk

Much of the industry's focus over the past year has shifted to settlement, clearing and operations as executives have become ultra-sensitive to analyzing trading data and investment positions to continually monitor and mitigate their risks, says Kevin McPartland, an analyst at TABB Group in New York. "The notion of the overnight batch shop is going away," says McPartland. Credit, risk and other systems that are updated regularly are now being analyzed periodically throughout the day by securities firms to identify trends or determine potential fraud in trading areas, says McPartland.
BI has also played a more prevalent role in compliance activities as broker/dealers are under tremendous pressures to demonstrate that they have auditable transaction trails for their trades, including information about the date and time of transactions--and the systems those transaction are conducted across--in case regulators should ever look, says Sinan Baskan, director of business development for the financial services industry at Sybase, whose customers include Citigroup, Barclays, Credit Suisse and Mitsubishi UFJ Securities.

Quantitative Analytics

Before mid-2008, many broker/dealers and investment banks were applying BI and analytics to longer-term investment planning where they might sift through six months of transactions to help determine one, three or five-year market trends, says McPartland. Now, decision-makers are demanding real-time market and credit reports on their Blackberries, regardless of whether the data is structured or unstructured in order to make decisions on investment positions or trades the same day. This includes the use of BI tools to help key stakeholders quantify the impact an SEC filing or a news report might have on markets or on the positions of individual instruments, says McPartland.

These types of analyses have also rekindled interest in the utilization of sentiment analytics, or the use of natural language processing to determine the emotional state of corporate leaders when they speak about the financial condition of their companies, says Gartner analyst Howard Rubin, who has a number of investment banks as his clients. In addition to Sybase RAP, other vendors selling sentiment analysis tools include The Parnassus Group, Attensity and Lexalytics. The demand for real-time information is playing out at Natexis Bleichroeder Inc. where demand for trading data has led the organization to load information from a daily basis to every hour and then every 30 minutes over the past few years, says Leonid Shteyngardt, director of data management and architecture for the New York-based broker/dealer.
Many of the firm’s 200 executives and traders are looking to analyze trade information and positions as well as data that’s tied to back-office processing, such as calculating accruals into trades and calculating the costs of settlements for trade economic analysis, says Shteyngardt.
More than half of the data the company loads into its Sybase data warehouse is used by executives and traders are for ad hoc requests, says Shteyngardt.
In a down trading environment, securities firms are also trying to apply BI to help them figure out how to wring more business from existing customers, says Michael Corcoran, senior vice president and chief marketing officer at Information Builders, a New York-based software vendor. For example, an investment bank that sells 401(k) services might apply BI it has gathered on its customers to explore where there might be additional trading and other cross-selling opportunities.
A few years ago, being the fastest to market with quantitative trading strategies was critical. But now, firms are equally concerned with the quality of the information as they look to hedge their risks.

High-Frequency Trading Strategies

BI is also being increasingly applied by firms to help them analyze their high-frequency trading strategies, according to Shahrawat. Although most firms keep these strategies close to the vest and don't want to disclose them in order to maintain a competitive advantage, a growing number of companies are focusing more attention on statistical arbitrage and developing high-throughput, low-latency applications where market data is collected and acted upon within seconds.
But to do that successfully, firms need to have an effective infrastructure in place, says Crosby. "If you can't capture 100 million trades you can't analyze 100 million trades," says Crosby. "Our ability to capture information is a real factor in our success," he adds.
Most database environments are too slow to support high-frequency trading requirements, says McPartland. This is where real-time BI tools can and are being applied, McPartland adds.
Companies are applying techniques such as time-series analytics and gathering information from exchanges and market data sources such as Bloomberg to help support their high-frequency trading strategies and quickly analyze prices and whether they fall within acceptable thresholds, says McPartland. But to do so effectively, data needs to be formatted in such a way for firms to be able to sift through thousands of orders per second, he adds.
"These quants [quantitative analysts] are always looking for an edge," says McPartland.
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