Neuro-fuzzy Data Mining for Target Group Selection in Retail Banking

Data Mining Algorithms are capable of ‘pressing the crude data coal into diamonds of knowledge’. Neuro-Fuzzy Systems (NFS) in particular promise to combine the benefits of both fuzzy systems and neural networks, and are thus able to learn IF-THEN-rules, which are easy to interpret, from data. Hence, they are a very promising Data Mining Approach. In this case study we describe how to support a bank’s new direct mailing campaign based on data about their customers and their reactions on a past campaign with a Neuro-Fuzzy System. We will describe how Neuro-Fuzzy Systems can be used as Data Mining tools to extract descriptions of interesting target groups for this bank. We will also show which preprocessing and postprocessing steps are indispensable to make this Neuro-Fuzzy Data Mining kernel work.