gallagher bassett: from mainframe to modern data capabilities and a new business model

With all of Gallagher Bassett’s claims processing data in a mainframe environment, it was impossible, due to systems limitations, to create raw data feeds and analytics in a short period of time.

As part of our strategy, we established a hybrid Azure cloud and on-premise solution, that allowed our client to provide modern and fast data capabilities on top of their current legacy environment. No significant changes were made to their existing environment. 

The boost in performance, reliability, and scalability enabled Gallagher to continue to grow at a non-linear rate without worrying about the technical limitations of their data reporting and analytics platforms.

Gallagher’s business objective was to make aggregate claims available to the customers and make it as easy as possible to consume it.

As a result of our work, we enabled clients, via a secure API, to request information for thousands of claims and insurance policies at an unprecedented rapid refresh rate of four times per day, exposing the data for on-demand data consumption. 

This new rate of processing information resulted in a new revenue model (and SaaS product), which continues to grow. Clients are now able to receive their claims data in an unprecedented time, with the new ability to quickly aggregate claims data as part of an additional offering.

 

A common misconception is that modernization always involves replacing legacy systems, hiring a ton of tech resources, and engaging in a multi-year digital transformation project. That’s not correct.

The migration to the cloud enables Gallagher Bassett to continue with their business innovation without the legacy systems acting as a limiting factor. Additionally, their new cloud infrastructure and API framework allow Gallagher to add new tools and services on top of this platform without worrying about their current legacy

We created a hybrid solution that joined Gallagher Bassett’s on-prem data centers with Azure Cloud. We leveraged the Azure Data Warehouse as the main platform and created data pipelines using the Azure Data Factory, to transfer data from on-premise systems to their new Azure cloud.

To make the transition possible, we went through a cloud provisioning and enablement process that met strict security requirements and ensured that the internal operations team was ready to manage the new cloud environment.