SetMETADescription("Analysis of public loan collectives");
SetMETAKeywords("Analysis, public loan banking, contract, saving amount, collective, model, simulation, data analysis"); ?>
and Planning")?> For more than ten years our group is in cooperation with the building and loan association LBS. Besides delivering expert opinions we developed methods and software tools for the analysis of large amounts of data for the Simulation of public loan collectives. In our projects we often encounter problems that can only be solved by a thorough mathematical analysis. People who are interested in topics for diploma theses or dissertations may visit our Themenbörse (still German) and/or contact us.
email@example.com Computing large amounts of data")?> In order to finance a building and loan association the structure of the whole group of savers, called a collective, is an important issue. Detailed analysis of the large amounts of data has become manageable in recent time only by the development of faster computers with larger memory. With new hardware methods and new mathematical methods we try to analyze the saving behavior of typical savers. At the same time we apply methods of cluster analysis to determine groups of savers with similar saving behavior. Most of the known cluster algorithms that we found are constrained to pools of 50 to 100 items and only a few features, whereas in our problem we have to deal with up to 2.5 million items and about 50 features. The goal of our cooperation with the building and loan association is the development of tools to analyze and predict the amount of savings over time based on the saving behavior of the past and current savers in the collective. Our knowledge is built into simulation models that predict the behavior of the collective. At the same time we gain insight into real saving behavior. To predict short-term and medium-term developments the principal influence is given by the current collective. Long-term predictions require an extrapolation of the current development of the collective together with external influences.