Automatic information extraction from scanned business documents is especially valuable in the application domain of document archiving. But current systems for automated document processing still require a lot of configuration work that can only be done by experienced users or administrators. We present an approach for information extraction which purely builds on end-user provided training examples and intentionally omits efficient known extraction techniques like rule based extraction that require intense training and/or information extraction expertise. Our evaluation on a large corpus of business documents shows competitive results of above 85% F1-measure on 10 commonly used fields like document type, sender, receiver and date. The system is deployed and used inside the commercial document management system DocuWare.