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Case-Based Reasoning (CBR) has been successfully applied in various domains over the years. Conservative adaptation provides a revision graph when partially modifying a subpar solution in contrast to null adaptation. Applying the complete CBR methodology towards financial reasoning provides a rather new domain for CBR and many opportunities to develop and improve a system when building it from scratch. Association models are gained by a target-driven method which provides an insight into the data. Rules for a reasoning prototype can be derived from the achieved associations. In this paper, initial achievements, the current state of the work and explanations regarding the system are demonstrated. Apart of that, an outlook regarding aspects within further work is presented.