Financial services
From Data Lab to 'Smart Data Factory
Starting point
- Managing non-financial risks requires a new data strategy
- IT and the Compliance department are seeking a way to collaboratively and iteratively implement data-based risk analyses
- Access to production data and tools should be made smart: fast, simple, feasible, usable, transparent, modular
- Compliance controlling aims to operationalise data science use cases
Procedure
- Design thinking workshops conceptualise 'Smart Data Factory' as the vision for an innovative data strategy
- The data strategy defines the target corridor with five guiding principles: infrastructure, data, roles, processes, technologies
- Implementation of a Docker-based infrastructure, enabling data to be packaged and flexibly transferred via containers, thanks to science tools and use cases
- Stress test through a complex use case verifies the data strategy of the 'Smart Data Factory'
Features/Project outcome
- The Data Lab develops ready-to-use containers with key use cases for the 'Smart Data Factory' as a think tank
- Encapsulating data and analytics tools such as R, PostgreSQL, RStudio, or Dataiku in containers ensures security and transparency
- IT and the business department work synergistically, result-oriented, and effectively based on the new data strategy
- The Data Lab innovates risk management, and containers make the data factory smart
Customer benefits
- The data strategy ensures synergistic collaboration between IT and the Compliance department
- Iterative and collaborative development of modular containers simplifies and accelerates implementation
- Innovation in the Data Lab and production in the 'Smart Data Factory' improve the quality of risk management
- The data strategy ensures transparency and minimises the bank's non-financial risks

Nico Inhoffen | Senior Manager