Become a data-driven bank with the right strategy

symbolic picture for data in retail banking with digital dots
  • Becoming a data-driven organisation with the methodology of Zühlke
  • Sustainable use of new technologies related to data and artificial intelligence
  • Development of a tailored strategic objective

Basellandschaftliche Kantonalbank, a Swiss retail bank, aims to become a data-driven organisation. A tailored strategy is developed together with Zühlke.

Data-driven banking

Basellandschaftliche Kantonalbank (BLKB) aims to develop into a data-driven organisation. To create the right strategic goals and guidelines for the bank, its management must tackle the following issues: What potential should be targeted in the transformation? How can this potential be implemented and what does the concrete implementation plan consist of? Based on its own methodology for data-driven companies, a core team supported by Zühlke develops the strategic objective tailored to BLKB.

Derived from the corporate strategy

The project’s starting point is a systematic assessment of BLKB’s current maturity with regard to data projects. Based on the corporate strategy, the core team derives focus areas for which added value is to be achieved through data. Specific use cases are developed and relevant development needs identified, while always taking the established data maturity of the company into account. This enables BLKB’s data strategy to be implemented through corresponding initiatives and projects.

Sustainable use of data

In only four months, the Zühlke team and BLKB developed an all-encompassing data & AI strategy and detailed, planned and budgeted a coordinated implementation roadmap consisting of use cases and company-wide measures. The technological, structural and procedural measures ensure the necessary prerequisites for implementing the project roadmap. The selected methodology ensures that all initiatives and projects in the data field are coordinated with each other and aligned with the corporate strategy. This avoids duplication, loss of efficiency and wasted time and aligns the company with sustainable use of data & AI technologies.