BLKB becomes a data-driven bank with the right strategy

Discover how Zühlke empowered Swiss retail bank Basellandschaftliche Kantonalbank (BLKB) to become a data-driven organisation, with the right strategy and execution.

Data-driven banking

Basellandschaftliche Kantonalbank (BLKB) wanted to become a data-driven organisation, with the capability to transform disparate data into real-time business value. 

To get there it needed a holistic strategy centred around two vital questions:

• Which opportunities must our data transformation enable us to realise, and what's our ultimate goal?
• How do we develop a concrete roadmap to get there, demonstrating impact as we go?

With a proven methodology and strong track record in empowering companies to become data-driven organisations, Zühlke was a natural choice in partner as BLKB embarked on its strategic data journey.

Translating corporate strategy into the right data roadmap

Our collaboration started with a systematic assessment of BLKB’s current data maturity and projects.

The core team reviewed the bank's corporate strategy and identified key focus areas and data initiatives with the greatest potential to deliver positive and tangible impact against the strategic roadmap. We developed specific data and AI use cases and identified the associated business, customer, and development needs.

These prioritised initiatives and projects, together with a measurement framework, provided the basis for BLKB's strategic data transformation.

Sustainable use of data

In just four months, the Zühlke team and BLKB developed an all-encompassing data and AI strategy, with a prioritised and iterative roadmap of use cases and company-wide measures.

The enabling technological, structural, and procedural measures we identified provide the necessary prerequisites for implementing the project roadmap. Meanwhile, the methodology we opted for ensures that all data initiatives and projects are aligned with each other and the overarching corporate strategy. This avoids duplication, loss of efficiency, and wasted time. Crucially, it aligns company strategy, with the effective and sustainable use of data and AI technologies.