The bank’s highly respected derivatives team is responsible for over one-third of the world’s total derivatives trades. Their derivatives practice has a global footprint with teams that support credit, interest rates, and equity derivatives in every region of the world. The bank has earned numerous industry awards and is recognized for its product innovations. Challenge With its significant derivatives exposure, the bank’s management recognized the importance of having a real-time global view of its positions. The existing system, based on a relational database, was comprised of multiple installations around the world. Due to the gradual expansions to accommodate the increasing data volume varieties, the legacy system was not fast enough to respond to growing business needs and requirements. It was unable to deliver real-time alerts to manage market and counterparty credit positions in the desired time frame. Solution The bank built a derivatives trade store based on the MarkLogic (a Big Data analytics solution provider) Server, replacing the incumbent technologies. Replacing the 20 disparate batch-processing servers with a single operational trade store enabled the bank to know its market and credit counterparty positions in real time, providing the ability to act quickly to mitigate risk. The accuracy and completeness of the data allowed the bank and its regulators to confidently rely on the metrics and stress test results it reports. The selection process included upgrading existing Oracle and Sybase technology. Meeting all the new regulatory requirements was also a major factor in the decision as the bank looked to maximize its investment. After the bank’s careful investigation, the choice was clear—only MarkLogic could meet both needs plus provide better performance, scalability, faster development for future requirements and implementation, and a much lower total cost of ownership. Figure 7.5 illustrates the transformation from the old fragmented systems to the new unified system. Results MarkLogic was selected because existing systems would not provide the subsecond updating and analysis response times needed to effectively manage a
derivatives trade book that represents nearly one-third of the global market. Trade data is now aggregated accurately across the bank’s entire derivatives portfolio, allowing risk management stakeholders to know the true enterprise risk profile, to conduct predictive analyses using accurate data, and to adopt a forwardlooking approach. Not only are hundreds of thousands of dollars of technology costs saved each year, but the bank does not need to add resources to meet regulators’ escalating demands for more transparency and stress-testing frequency. Here are the highlights: • An alerting feature keeps users appraised of upto-the-minute market and counterparty credit changes so they can take appropriate actions. • Derivatives are stored and traded in a single MarkLogic system requiring no downtime for maintenance, a significant competitive advantage. • Complex changes can be made in hours versus days, weeks, and even months needed by competitors. • Replacing Oracle and Sybase significantly reduced operations costs: one system versus 20, one database administrator instead of up to 10, and lower costs per trade. Next Steps The successful implementation and performance of the new system resulted in the bank’s examination of other areas where it could extract more value from its Big Data—structured, unstructured, and/or polystructured. Two applications are under active discussion. Its equity research business sees an opportunity to significantly boost revenue with a platform that provides real-time research, repurposing, and content delivery. The bank also sees the power of centralizing customer data to improve onboarding, increase cross-selling opportunities, and support know-your-customer requirements.
Questions for Discussion
1. How can Big Data benefit large-scale trading banks?
2. How did the MarkLogic infrastructure help ease the leveraging of Big Data?
3. What were the challenges, the proposed solution, and the obtained results?