Customer contact at banks and insurance companies: Modern data management should fulfill these 7 requirements

Data gaps often go unnoticed until they become a stumbling block in customer contact. Why excellent customer experience (CX) needs more than just good tools – and what requirements banks and insurance companies should really place on their data management. 

Many banks and insurance companies work with established CX systems – and assume that they are ideally positioned with them. However, if you take a closer look, you will notice that there are still too many gaps in data availability that cause customer experiences to falter. 

„I’m sorry, I don’t see it in the system.” A phrase that is repeated time and time again in everyday life – although the form has long since been filled in, the contact has already been registered or the preference has been saved. The cause is rarely a lack of willpower, but rather due to data management: An address is not synchronized. An event is not assigned to the customer. A system is not connected. 

These details determine how professional a company looks and how effective the service is. So how can it be done better? IT managers and decision makers should pay particular attention to these aspects when it comes to data management. 

Without consolidated and harmonized data records, every CX initiative remains fragmentary. In many companies, master data, communication histories and transaction information are managed in separate data silos. The result: duplicate entries, inconsistencies and manual reconciliation. A bank that stores customer contacts in e-banking, CRM and call center systems at the same time runs the risk of contradictory statements when providing advice. A well thought out data structure avoids this and forms the basis for automation, segmentation and transparent decision-finding.

Modern data management must not only be comprehensive and integrated, but also of high quality. Outdated, incorrect or duplicate data records lead to delays, misunderstandings and inefficiency in day-to-day operations. Clear validation logic, duplicate matching and regular data hygiene not only ensure efficiency, but also trust. 

Data must be available in full and in context at the moment a decision or a contact is made, regardless of the channel and without delay. In practice, this means, for instance, that a customer advisor on the phone immediately sees that the customer submitted a claim online a few minutes earlier. Or that during a branch meeting, a customer advisor can immediately see which offers the customer has recently received via email. 

Keywords GDPR, FINMA and BaFin: In an environment with strict regulatory requirements, it is essential that companies retain full control over their data. This includes not only storage and data processing locations (e.g., Swiss or European cloud), but also the ability to react to changing European requirements at any time. An insurance company must be able to prove which consents have been given for data processing and how long certain information has been stored in an audit-prove manner. 

When decisions are increasingly being made automatically, for instance through AI-supported product recommendations or risk assessments, these decisions must remain traceable. This is not only a legal requirement, but is also central to the customer relationship. For example: A customer receives a loan rejection by email. In the event of an enquiry, the bank must be able to clearly explain the criteria on which this assessment is based – even if an algorithm was involved. Transparent data storage creates security both internally and externally. In addition, ethical standards firmly anchored in the company increase trust. 

Data architects have to keep pace with business development: New products, increasing data volumes, additional locations or new regulatory requirements must not trigger a conversion project. Anyone introducing a new sales channel today, such as video consulting, should be able to integrate it into the existing system landscape without any major integration effort. Even an increasing number of users, for example through partner sales or broker portals, must not impair performance.

AI applications, such as chatbots, virtual assistants or next best action engines, can only work reliably if they can access complete and up-to-date data. If, for example, in the case of an insurance policy, the current risk assessment or a recently reported claim is missing, the chatbot cannot provide correct information – and thus immediately loses credibility. The quality of AI depends directly on the quality of integration. Data that lies dormant in silos is simply invisible to AI. 

This is where the BSI Customer Suite comes into play: It combines all the elements that are required for excellent service – modularly, integratively and sovereignly. As a central hub for CRM and CX, it creates a consistent data landscape across all touch points – from lead routing to AI-supported decision-making aid.

For banks, for example, this means that advisors can have a 360° customer view in real time with information from e-banking, branch visits, call center interactions and marketing campaigns. This makes it much easier to prepare for meetings. 

In the insurance sector, the Suite, for instance, enables a seamless claims process without media discontinuity. Customer enquiries are automatically assigned, mapped in the central interface and can be processed across all channels. 

Customer centricity does not start with the customers, but with the right architecture. If you want to provide real service, data management must be a strategic priority. Structure, availability and control are not mere technical details, but form the basis for convincing customer interactions. 

With BSI Software, companies remain sovereign, free in their technological choices and can scale without disruption, so that the phrase “I don’t see it in the system” becomes a thing of the past.