Data quality: Swiss banks with optimization potential

A new study by the Lucerne University of Applied Sciences and Arts shows: Management of data quality and quantity is also a highly relevant topic in banking. At the same time, many banks state that they do not comment on this topic because this would reveal too much about their business activities. The study was conducted by the Institute of Financial Services Zug IFZ together with BSI (Business Systems Integration AG), Dun&Bradstreet as well as Finnova and msg GillardonBSM. It examined how well banks are prepared for the upcoming challenges in customer management and the upcoming leap in technology. The study analyzed the connection between data management and the resulting opportunities to increase the business success of banks in a sustainable and automated way. It also aims to elicit the challenges and opportunities for banks that arise from qualitatively and quantitatively excellent data management. To this end, the researchers surveyed the largest 70 banks in the DACH region from May 2021 to September 2021.

High data quality and quantity: benefits show up with a delay

"If we look at the size of the participating banks, we see that small and very large banks in particular maintain dedicated teams for customer master data management," notes Nils Hafner, author of the study and lecturer in customer management at the Institute of Financial Services Zug IFZ at the Lucerne University of Applied Sciences and Arts. This could be due to the fact that medium-sized institutions in particular do not yet see the need for consistent data-based management of the customer base as a success factor. The same applies to anchoring master data management in the corporate strategy. "Since the specific benefits of high data quantity and quality only become apparent over time, we assume that banks in the DACH region are just beginning to understand fundamental connections between knowledge in the form of data and skill in the form of successful campaigns," says the study leader.

Data management as part of the business model

When it comes to deriving concrete recommendations for banking institutions from this study, these are not necessarily based on developments within the industry. Particularly in the context of participating in and shaping ecosystems, banks are often not in the position of the orchestrator of such an ecosystem, as the study authors note. These are often shaped by industries closer to the customer, such as retail. Drawing from this, the study recommends that banks increase their knowledge of how to collect, store and analyze key customer data categories. This means in detail:

1. Banks should think about the strategic importance of customer knowledge and thus about the collection, storage and analysis of customer master data for their own business model. This includes an analysis of the current situation, i.e., a customer data quality assessment, and the derivation of measures to increase the quantity and bring the data quality to an acceptable level. Essential here is the formulation of strategic principles for data management, such as the requirement for a complete 360° customer view, the principle of error-free recording "first time right," the establishment of a "single source of truth" or the "golden record," and the idea of "zero maintenance" through a high degree of automation in the quality management of the customer master data.
2. Particularly in the context of the first principle of a complete 360° customer view, it is important to abandon traditional priorities in the touchpoint and channel view of financial institutions. The study clearly shows here that banks still distinguish between the "physical customer" via telephone and branch and the "online customer on the net". However, a holistic customer view can only be established if the "classic-physical" observation of customer behavior is supplemented with the "digital" click behavior of customers in e-mail campaigns or on the net. Only in this way can the interests of the clientele be analyzed holistically.
3. Overall, financial institutions must become faster and better at understanding the lives of their customers. Compared to the insurance industry or retail trade, they are often not in a position to identify and react to changes in their customers' lives in real time and in a fully automated manner. As a result, they are also unable to analyze and leverage customer potential for cross- and up-selling in the medium term. However, if the other sectors mentioned above succeed in doing this, they will take some of the business volume away from the traditional banks.

Finally, it can be stated that banks are still at a surprisingly low level of maturity in customer data management and should urgently develop accordingly if they want to be successful in competition in an increasingly digitalized world.

Source and further information: Lucerne University