This bachelor thesis deals with the development and implementation of a customized data validation solution to streamline the validation process, ensure compliance with and manage the growing data complexity associated with Baloise’s Group Solvency II reporting. The research conducted as part of this thesis includes an extensive literature review on data validation techniques, regulatory requirements and existing validation processes of the insurance industry.

Based on this, an efficient, user-friendly and customizable data validation tool was developed to meet the specific requirements of Baloise Group. This tool, crafted with the capability to incorporate EIOPA validation rules and user-specific validation requirements, was built using Python and Pandera, a built-in Python library. The code provides a standardized, user-friendly interface, through which the user can check the correctness of the data against the associated EIOPA validation rules.

The methodology used in this project involved a sequential, iterative process that included Analysis, Planning, Development, and Testing phases. Development focused on the use of Python and Pandera for programming data validation functions, a container environment for executing the functions and standardizing input syntax to ensure usability. The solution provides a scalable framework that can accommodate potential future enhancements and adaptations to changing regulatory requirements. This work demonstrates the effectiveness of custom data validation solutions in the insurance industry and contributes to the field by providing valuable insights and a practical, adaptable tool for improving and streamlining reporting processes.