Financial institutions are among the largest commercial consumers of high-performance computing (HPC), and for good reason. HPC provides the foundation for valuable analytics important to financial institutions, embracing: trading (high-frequency and algorithmic); risk management; pricing and valuation of securities and derivatives; and business and economic analytics, including modeling and simulation.

The pressures to provide accurate, reliable financial analytics will push more financial institutions in the direction of HPC. Their veteran technologists will look for more efficient technologies for getting greater insights. For capital markets, providing real-time data and analysis — faster and at a lower cost — to make informed decisions is critical.

That is certainly true when competitors are gathering more and more data and getting increasingly creative with sophisticated approaches for technology application — as when UBS Investment Research used satellite surveillance of 100 Walmart parking lots and gathered data on the number of cars parked in those lots month after month. From space, analysts got a much different and more accurate picture of the company’s quarterly earnings than traditional methods did, based on the traffic surge the satellite images revealed compared to the previous year.

Thanks to new technologies, HPC continues to evolve, and big data is leading the charge. Indeed, the evolution of big data has affected almost every industry. It’s no surprise that the financial community has embraced it so avidly.

Read “The Seven Keys to Successfully Managing Compute Workloads at Financial Institutions” Solutions Brief.

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