Case Study: FX and Benchmark Automations

It has only been a week since we began working with our newest client and we are pleased to report that we have already finished the latest implementation of Connect. We have migrated, tested, and integrated our way into production thanks to the flexibility of our data integration platform. We thought we would spend two minutes telling you a little bit more about it and showing you what Connect can help your organisation achieve.

What were we trying to solve?

Our clients have a subscription to Bloomberg’s foreign exchange and benchmark data. Before Connect it was being delivered in the form of CSV files which were then manually uploaded into their eFront system. Not only did this consume valuable time and take significant effort, but it was also vulnerable to both user input errors and key person risks that directly impacted downstream systems.

And so, our client’s requirements were simple. They wanted to automate the ingestion of Bloomberg data and feed them automatically into eFront. Without the need for any manual intervention.

What did we do?

Working together with our client, we identified the key data points that required integration, the mappings into eFront and the cadence of the integration. From there our Connectors made short work of the task. Our Bloomberg connector picked up the data and schema and added them to the connector’s configuration. Next, we configured the eFront connector to direct the data to where it was needed. Finally, the required mapping was overlaid, and our pipeline was complete. Following a complete testing phase, we redirected the connectors to the production environment and went live.

What did we solve?

From a technical perspective, we have simply automated the ingestion of foreign exchange and benchmark data. Our Connect platform takes in the Bloomberg data and feeds them into eFront on a prescribed schedule. From a business user’s perspective, we have solved so much more. Users of eFront no longer need to chase for FX and benchmark data or wonder if differences in metrics are caused by a lack of up-to-date data. This allows users to focus on their actual work, rather than the requirement of being an occasional data auditor.

Apples and Pears

Our connectors all talk to each other, and this means that the FX and benchmark data can also be ingested by other systems across the firm. For our client, this means better business decisions. And, of course, this consistency in data means that no matter how they slice (and dice) the data, they can be supremely confident that everyone in their organisation is comparing apples with apples (and should they wish, pears with pears).

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