Case Study

Using MDM to achieve regulatory compliance and add business value

Our client, a global organisation with annual revenues in billions of dollars, provides finance, lines of credit and insurance products to their customers. Given the highly regulated environment in which they operate, it is crucial that they remain compliant with the ever-evolving regulatory landscape. To help with this, they engaged DTSQUARED to implement a multi-stage Master Data Management (MDM) project as part of the wider Data Strategy we are supporting them with.



Our client operates in a highly regulated environment that is ever evolving, with the added complication of having to report to multiple regional regulators, and therefore needed to ensure that their management of customer data fully satisfies reporting requirements. We helped them achieve this by:

  1. Replacing an outdated customer database with a robust and scalable MDM solution.
  2. Building a project delivery team made up of resources from both the client and DTSQUARED, supporting seamless knowledge transfer and opportunity for on-the-job training.
  3. Tailoring the tools and technologies used to serve their unique business goals.


In order to build and deliver a solution that fit our client’s requirements, we took the following steps:

  1. Applied Informatica’s MDM technology and used the Informatic Data Quality (IDQ) tool to manage the ETL process.
  2. Introduced workflows to automate the testing of high volumes of data and implemented an MDM dashboard for reporting operational metrics.
  3. Designed their MDM model to retain pre-existing customer IDs and replicate source tables, which saved time and ensured an easily traceable data lineage.


We delivered impressive tangible results that aligned with our client’s overarching business objectives and provided a foundation for multi-year data-led change.

A new MDM model was successfully implemented, not only helping to satisfy strict regulatory requirements, but also providing opportunity to better utilise customer data to extract real business value.

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