Data Science and Big Data Analytics in Financial Services: A Case Study

Background

Foreign exchange markets generate large volumes of data. Some of the information hidden within these interactions could be valuable to market participants. In the past there were limitations on accessing some of this data. In recent years analytics technology has developed to the point where companies are able to extract insights from such data.

Financial organizations may need to use streaming analytics (which operate in real time) in conjunction with historical data from conventional business intelligence systems if they are to improve retention and identify potential clients, both retail and institutional. This integration allows for customer profiling, not just to personalize offers but to achieve more optimal timing. In foreign exchange markets, where an institution wants to check thousands of transactions per second, streaming analytics can enable it to narrow the focus and monitor the success rate in quoting foreign exchange prices to potential customers.

Historical analysis can reveal a particular customer's usual transaction size, timing and individual price point relative to a median in the market. Dynamic pricing that ensures a profit on a specific transaction at a specific time, while meeting the customer's likely requirements based on their profile, requires the use of real-time analysis.

The use of streamed real-time data is becoming increasingly common. In the development and marketing of foreign exchange products, the typical foundational capabilities we might see include predictive customer intelligence and big-data analytics, coupled with enterprise marketing management.

Banks already have large quantities of real-time data that they analyze for very specific needs as dictated by their current analytical capabilities, which have been designed to allow the users to carry out broadly predetermined analyses.

Deutsche Bank for example uses a big-data application called FiREapps to aggregate, validate and analyze underlying exposure data from corporate customers. Its FX trade execution services customers then use the results of this analysis to manage their overall currency exposures and ensure their trades are compliant with corporate foreign exchange policy.