Operational process improvement
One of the largest and most efficient FX trading businesses wanted more: to improve its market leading 98.5% STP rate.
As one of the market leading global FX businesses, the data set was large. Three months of data generated a 90+ mm row file from a single system, with several others of 20+ mm.
The client had an existing data analysis infrastructure but its functionality had to be throttled back due to the data’s complexity and size.
Multiple trade versions, not all of which would be present in all systems; trade IDs that could be amended and multiple aggregation levels added further complexity in a tens of millions of rows data set.
The project required a new approach.
Designing the analytical approach
CPRA’s data tools, that can be wielded by business users without coding experience, allowed us to connect disparate data sources to clean and tag data and easily join across and between aggregation levels.
No data warehouse. No data model required. Or functional specification. Or detailed BRD.
We also used modern data visualisation tools to help the data analysis and data story.
Data analytics value creation
20+ headcount reduction from efficiency gains.
Our client’s senior management was provided a view of their business which they had not seen before. It allowed them to adjust the operational model to reduce cost and improve process efficiency.
The resulting data model could be implemented in production and run on an automated basis, with alerts based on business rules to detect upstream exception causing events.