Data Quality Capability Assessment for Financial Institutions

Capgemini’s Data Quality Capability Assessment Service helps our financial services clients identify which processes and platforms need to be established or modified and gain a roadmap for making the required changes and raising organizational awareness.

Challenges today

Regulatory and other business problems today are often caused by the underlying data. Your company may be accepting unnecessary costs and even risking heavy regulatory penalties as a result of poor-quality data. On the other hand, high data quality brings major benefits, such as better-informed decisions and more effective cross-sell and up-sell.

Today, increasingly stringent regulations across the US and Europe dictate a more coherent data quality management approach that operates across the enterprise. The first step is to establish a baseline understanding of the institution’s maturity with respect to data quality.

Introducing an approach like this requires a lot of time, money and effort. Before embarking on such a major investment, it just makes sense for an organization to get a clear picture of the current state of its data quality. Capgemini offers a service that can help you get that clear picture fast: Capgemini’s Data Quality Capability Assessment.


Our quality assessment results in a comprehensive picture of an organization’s current data quality management capability and processes, making it possible to identify any gaps. In addition to raising awareness of data quality issues among business, operations, and technology stakeholders, the quality assessment also provides the basis for creating the necessary statements of vision and goals and a roadmap for reaching those goals.


We tailor the assessment to each client’s needs, but the process usually includes the following:

  • Define the target state, in close collaboration with client leadership.
  • Understand the current state, and identify the gaps against the target state.
  • Define a best-practice approach for assessment of the maturity of data quality activities, and for remediation as needed.
  • Identify initiatives required to improve the overall data quality process to the point where it can support future business needs and regulatory mandates.
  • Create an implementation roadmap for carrying out these initiatives in order to fill the gaps identified earlier.
  • Establish a governance process for implementation of data quality initiatives.

Take the first step today towards an enterprise-wide approach to data quality management by contacting us at or reaching out to one of our experts.