State of the Art of Financial Decision Support Systems based on Problem, Requirement, Component and Evaluation Categories

Financial decision support has become an important information systems research topic and is also of highest interest to practitioners. Two rapidly emerging trends, the increasing amount of available data and the evolution of data mining methods, pose challenges for researchers. Thus, a review of existing research with the goal to guide future research efforts in this domain is timely. To structure our literature review and future research in this area, we propose a framework in the paper that integrates elements of decision support systems, design theory, and information mining. The framework is then applied in the paper. Our analysis reveals that the focus of existing research can be grouped into three major domain categories. More research is needed in two of the categories for which we found only very few IS studies, despite the high relevance of these topics due to increased turbulences in worldwide financial markets. Furthermore, we discuss the opportunities to make stronger use of heterogeneous data and of combined data mining techniques and to build upon the rich set of available evaluation methods.