Financial institutions have large amounts of data at their disposal, which should be used optimally for the benefit of the companies and their customers. For this, it is crucial not only to know what data is available and where it is located, but also to be able to make statements about the quality of the data. Top management in particular depends on this in order to be able to make well-founded decisions on the basis of this information.
But how can data quality be measured and presented in a way that is simple and comprehensible for everyone? This is the question our experts addressed as part of a project for Pfandbriefbank (pbb).
Comprehensible and reliable statements on data quality enable management to draw conclusions for well-founded decisions.
Data Quality Score
The task was to develop a solution that would enable the top management to get a picture of the quality of the data of the entire bank. For this purpose, the project "Data Quality Reporting" was set up together with the client. The goal: to make data quality measurable, to reduce complexity and to give the right impulses to the final decision-makers.
In our approach to making something abstract like data quality presentable, we took our cue from the food industry: The Nutri-Score printed on many packages gives consumers a quick and easy-to-understand impression of the nutritional values of the individual ingredients of food and can be a decision criterion when choosing a product.
Why not use something like this in the form of a data quality (DQ) score for data?
Marco Lenhardt
Partner, Financial Services
KPMG AG Wirtschaftsprüfungsgesellschaft
Florian Woy
Senior Manager, Financial Services
KPMG AG Wirtschaftsprüfungsgesellschaft
Individually calibratable approach
In order to approach a quality label on the state of the data, a scoring approach with model parameters was chosen. A quality profile for control-relevant key figures was determined from numerous sources, based on various DQ assurance measures along the data flows. The calculation and aggregation logic enables the assignment of a data quality score both at the key figure and report level. The label is intended to be an easy-to-understand but not simplistic assessment of the quality of data.
Dynamic data quality report
The top management, but also all other employees of the Pfandbrief Bank, can view the assessments of the status of data quality in a bank-wide DQ report (dashboard), which allows individual presentations and evaluations - depending on the required perspective.
We have set up a DQ reporting system that is suitable for the target group and that everyone can use according to their needs. Since it is visually easy to understand, it is very well accepted in the company.
For more information on the project for Pfandbriefbank, watch the video below:
