Survey – Data Management Office Maturity

Data Management

Aurexia has lead during first semester a study on data management offices maturity.

The objective of this study is to perfom an analysis to understand how financial services are collecting, handling and managing the data with their data management offices to highlight the benefits, challenges and the best practices.

23 interviews have been done with different profiles : Chief Data Officers, Data management responsibles, Data quality managers,…of main banks and insurance companies in France, Luxembourg, Italy and Hong Kong.

6 topics have been adressed:

  1. Data governance
  2. Data dictionary
  3. Data quality
  4. Data lineage
  5. IT Architecture
  6. Ambition

For more information about our study or to get the full copy, please send us an e-mail

Main results

Data Gouvernance

2 main areas can be used to measure Data Governance :

  • The perimeter / scope which is not limited to regulatory anymore
  • The Roles and Responsibilities which are evolving with the increase of DMOs tasks

Data Dictionary :

The harmonization of data dictionary between local and central still remains an important topic. The difficulty is to ensure that all business lines share the same DNA related to the final usage of data but with keeping the different specificities (commercial, risk, legal, business, finance, regulatory)

Data Quality

Following a common nomenclature, data quality indicators have been developed and reviewed in dedicated committees. However, some issues remain (discrepancies between business lines, methodologies, etc.)

Data Lineage

The most complex subject is the data lineage because it requires significant investments in IT solutions and data need to be plug to IT systems and adaptable to changes.

Architecture IT

Projects related to Data Quality and Data Lineage have particularly strong adhesion with the technical and functional architecture. Data approaches provide an opportunity to optimize and streamline IT, which can result in tool decommissioning or convergence of data flows (e.g. risk and finance).