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