Selected business intelligence methods for decision-making support in a finance institution

Abstract

This article deals with decision-making support methods’ implementation in a medium size financial company with international operations. The objective of this article is to show the abilities of these methods to precise decision-making of management. At the beginning of this article there is briefly described the existing situation in this business sector in Central Europe. After that part Business Intelligence methods are described as well as the reasons while these methods have been introduced in small and medium enterprises. These methods are dependent on data, on acquisition of data and on validation of this data. Pre-processed data can be used for standard reporting. Utilization of this type of reporting is described on two examples in this article. These examples show dependences between exchange rate volatility and a specific period of the year. Then follows a demonstration of client classification - firstly on historical data from years 2010 to 2013 utilizing a cluster analysis. New clients have then been provisionally allocated to already designed groups thanks to the above-mentioned description of clusters. When the external environment changed, due to primarily the Czech National Bank interventions, it has been essential to design better classification methods for new clients. These methods are described in this article and results of these classification methods are compared.