The KNF guidelines on data management

The KNF guidelines on data management, focusing on the management of information technology areas and the security of teleinformatics environments in insurance and reinsurance companies, emphasize the importance of formalizing data quality management practices. These guidelines suggest that each company should have structured data management policies, which should be tailored to the company’s size, risk profile, and specific business needs.

In practice, data quality management should be a continuous process of defining the quality parameters that meet business requirements while ensuring these parameters are consistently upheld. The guidelines suggest that the level of detail and scope of data quality management should depend on the scale of operations and the importance of different data groups within the company.

The implementation should focus on regular assessments of data integrity, periodic audits, and the introduction of processes to monitor and ensure data consistency and security across all systems within the company.

The implementation process begins with data inventory. The inventory allows for the collection of all information regarding the data processed within the organization’s operations. The result of this process is the identification of specific data sets, the sources of their origin, the processes they relate to, and the owner responsible for their processing. Conducting the inventory serves as the starting point for creating a data quality management process, followed by the enhancement of this process with the deployment of IT tools that enable data quality checks.