Financial Services Solutions

Financial Services

In Financial Services, data capture, algorithmic trading, backtesting, risk management, pricing and fraud detection, competitiveness depends on speed and volume.

Hedge funds, proprietary trading firms and major banks are discovering that DDN’s massive parallelism, real time architecture and ability to scale up or out deliver:

  • More test iterations, against more data in less time for more profitable trading strategies… Faster
  • Calculate VaR for Thousands of securities in seconds for accurate, actionable intra-day risk measurement
  • Faster, consolidated analytics for mixed IO for in-transaction “envelope” fraud identification

Featured Webinar

Building the Future of Financial Services with AI

In this hyper-competitive industry saving microseconds directly translates into opportunity. Hedge funds, proprietary trading firms, and major banks are benefiting from DDN A³I® with NVIDIA DGX™ systems to optimize operations, innovate, and unlock more profit faster. Hear our financial services industry experts discuss how optimized infrastructures give finance institutions the biggest return on investment for AI enabled-data centers.

“With our SAS  solution (on DDN parallel file system appliances) we achieved 452% faster workflows across the board—some applications were even higher. We also went from over 100 [SAS] servers to 16 for the entire enterprise.”

John Eubanks
Systems Engineer V, Fannie Mae

Use Cases

  • A Large U.S. Proprietary Trading Firm consolidated Kx® servers for 10x faster performance than NAS and cost-effective, scalable support for multiple functions in a multi-tenancy environment using DDN parallel file system appliances.
  • A Well-Known Online Payment Service used DDN’s 2 -7x Hadoop® performance advantage to reduce fraud detection times for credit card transactions to under 200ms – stopping $100s of Millions in credit card fraud per year.
  • Investment Banking Arm of a Large International Bank scrapped their high-end enterprise SAN because it failed to scale and was operating at only 1/3 desired performance after 1 yr in operation. Moving to DDN parallel file system appliances reduced key analytics tasks by up to 80%.

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