Grid Computing for Financial Services
With AWS, organizations use Amazon EC2 to spin up compute resources to instantly meet peak processing demands and de-provision after the workload is complete.
AWS offers a range of storage services and solutions to support both application and archival requirements. Select from object, file, and block storage services.
Big Data Solutions
AWS offers the most comprehensive suite of big data services to handle every step of the analytics process chain to get to actionable, data-driven insights.
Variable Instance Types
Amazon EC2 supports different instance types that comprise varying combinations of CPU, memory, storage, and networking capacity—optimized for your application.
AWS' pay-as-you-go model offers 4 EC2 pricing instance structures to enable cost efficiencies—On-Demand, Reserved, Spot, and Dedicated Hosts.
Sample Reference Architecture for Grid Computing
To help you get started, access a sample reference architecture of a grid computing solution that many of our Financial Services customers are deploying in their respective environments.
This configuration of AWS services enables on-demand capacity so users can shut down their workloads when jobs are completed. Customers can also take advantage of advanced features, such as transient clusters or auto-scaling clusters that allow environments to expand and contract depending on your job load.
Capital Management and Reporting
Regulations such as CCAR, Solvency II, and FRTB require organizations to report capital positions, which calls for increased demand and frequency of simulation-based calculations for market, credit, and counterparty risk.
Risk Management Portfolio Optimization
Flexible grid-computing capabilities allow portfolio managers to conduct simulations that: 1. identify risks within their portfolio of products, hedging opportunities, and areas for optimization; and 2. model the impact of hypothetical portfolio changes.
Contract Pricing and Valuation
The industry relies heavily on simulations for pricing and valuation of financial products, including credit and interest rate derivatives and variable annuities. This requires stochastic models with heavy use of Monte-Carlo simulation methods.
Product and Strategy Development
The development of new financial products requires extensive historical back testing and market simulations. Being able to spin up a development environment instantly with AWS is also a benefit that can accelerate product deployment.
Case studies and resources
“We can run all 5 million policies in minutes, instead of the standard overnight run times. We can get a very accurate and unique picture of our customers’ market risk exposure — and there is no other solution that offers better performance at a lower cost for this business.”
- Peter Phillips, Managing Director, Aon
“We began our journey with AWS on our high performace compute cluster needs. It was made to order, hand-in-glove so to speak in terms of having a need for variable compute at a moment's notice. So rather than build the chapel for Easter Sunday, we can have just-in-time computing.”
John Trujillo, Assistant VP of Technology, Pacific Life
“We require enormous computing power to quickly and efficiently analyze the risks of derivatives and use them in trading, and I think that it would not have been easy to respond if it were not for AWS.”
Dr. Jeong Ho Chu, Management Team, Yuanta Securities
Learn about getting access to thousands of processors with connections and tools to help you easily create your grid computing cluster.
Grid Computing for Risk Management
Learn how Financial Services organizations can leverage AWS grid-computing capabilities to perform large-scale calculations for risk management purposes.
Grid Computing for Financial Services
This whitepaper shares best practices for managing large grids on the AWS platform and offers a reference architecture.