Data analysis and data management in banking are still mainly focused on supporting internal processes. In the age of digitalization, however, customer data is critical to the success of the majority of companies and financial service providers. The essential goal is to transform into a data-driven or data-driven organization – and to consistently align with customer needs.
In corporate banking in particular, customer data can be used specifically to analyze customer needs on the one hand and demand behavior on the other. The first step involves the use of big data analytics technologies, which enable data-based decisions to be made and this data to be integrated into business processes in a way that adds value. In addition, intelligent algorithms are used to perform much more complex data analyses than before and to train and “teach” so-called machine learning systems. This means that these systems will later be able to recognize patterns and regularities in large volumes of data on their own and make autonomous decisions, for example when it comes to providing tailored investment offers or financing options for a specific corporate customer.
