Financial Services: Technical Computing Solutions

From high frequency trading to business and economic analysis, risk management and the pricing and valuation of financial instruments, automation is rapidly innovating the financial services industry. These financial services are driven by the need for speed, and as a result impose demanding requirements on the compute infrastructure.

High frequency trading needs low latency and high throughput. Even microsecond-scale delays in a trade could result in very large financial losses. Conversely, risk management is a very compute intensive task, applying complex mathematical models with thousands of variables to determine the real value of the underlying financial instruments.

RAID Inc., with more than 20 years experience developing customized technical computing solutions, is the perfect partner to help build the next generation financial modeling and trading infrastructure to gain a competitive edge in maximizing productivity and quicker time to results. As specialists, our team has extensive experience in the industry building and maintaining custom solutions designed specifically for compute and network intensive tasks such as risk management and high frequency trading.

The company understands that financial modeling systems requires not only very dense storage systems, but systems that provide consistency and predictability of transaction performance. As important as storage, the network must be able to handle both high frequency transactions and large data transfers. The compute power is critical to the success of financial services firms. Some risk modeling lends itself to parallel execution, while other models only work with sequential execution. Thus, servers must be designed to work both standalone and as part of a cluster.

RAID Inc.’s vendor-agnostic customized technical computing solutions have enabled our customers to successfully develop complex financial models. These models are updated very frequently, allowing customers to evaluate and reduce risk, reduce cost and increase productivity and revenue.


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