Financial Services organizations, from fintech startups to longstanding enterprises, have been utilizing batch processing in areas such as high performance computing for risk management, end-of-day trade processing, and fraud surveillance. You can use Amazon Batch to minimize human error, increase speed and accuracy, and reduce costs with automation, so that you can refocus on evolving the business.
High performance computing
High performance computing
The Financial Services industry has advanced the use of high performance computing in areas such as pricing, market positions, and risk management. By taking these compute-intensive workloads onto Amazon Web Services, organizations have increased speed, scalability, and cost-savings. With Amazon Batch, organizations can automate the resourcing and scheduling these jobs to save costs and accelerate decision-making and go-to-market speeds.

Post-trade analytics
Trading desks are constantly looking for opportunities to improve their positions by analyzing the day’s transaction costs, execution reporting, and market performance, among other areas. All of this requires require batch processing of large data sets from multiple sources after the trading day closes. Amazon Batch enables the automation of these workloads so that you can understand the pertinent risk going into the next day’s trading cycle and make better decisions based on data.

Fraud surveillance
Fraud is an ongoing concern impacting all industries, especially Financial Services. Amazon Machine Learning enables more intelligent ways to analyze data using algorithms and models to combat this challenge. When used in conjunction with Amazon Batch, organizations can automate the data processing or analysis required to detect irregular patterns in your data that could be an indicator of fraudulent activity such as money laundering and payments fraud.