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Business2
Business2

BBVA: Evolution towards a Data Driven organization

The BBVA Group is immersed in the transformation process towards a data-driven organization. In Corporate & Investment Banking, the necessary steps are being taken to make this evolution a reality

In this era of digital banking where everything seems to have been invented, there is still an area in which much remains to be done. In the words of Sergio Fidalgo, Head of CIB Engineering at BBVA, the biggest gap in the digital transformation is in data treatment.

The BBVA Group is immersed in an evolution process towards a data-driven organization, a challenge to adapt to an environment in which data has an incalculable value.

This ambitious project, set as a priority in 2018 by the CEO of BBVA himself, Carlos Torres, will help financial organizations evolve in the long term.

What are the implications of this new model?

Data-driven is the change from a traditional organizational culture to a data-based culture, that is to say, a company where decision-making is determined by data rather than by intuition, experience or the actions of competitors. The data becomes the core of the creative process and the main source for the generation and adaptation of financial products and services.

At an organizational level, it entails the creation of new teams: to date, the Data Portfolio Manager and Data Domain Office units. The Government of Data Office stands out among them, a key strategic line of the BBVA data agenda.

In relation to the technological model, BBVA has opted for Datio, as the new big data infrastructure of the group, which supports the data-driven model.

New Roles

The new organizational model also involves the creation of certain specific roles:

  • Data Scientist: a profile responsible for studying the data intelligence, developing the necessary tools and skills for the study of advanced analytics, and ensuring that the information is available in the new analytical environments.
  • Data Owner: an interesting feature of the new data governance model is its decentralization. In a way, workers are responsible for the correct use and storage of the data, which must comply with a series of principles:
    • Correct content.
    • Quality: reliable information.
    • Lineage: knowledge and documentation of the life cycle of the data.
    • Availability: accessibility to the data by the entire organization.

To Ensure the quality, accuracy, and storage of the data“, is an almost utopian goal that promises a before and after in the financial organization after the implementation of this ambitious global project.

Many new projects focused on the improvement of data will emerge from this one, and Nfq will be part of it.

This post has been written by Rosa Losada Díaz
Consultant at Nfq