On the Financial Situation Analysis with KNN and Naive Bayes Classification Algorithms

Classification, a data mining technique, has been applied on the financial parameters usedin the Altman Z-Score formulas for a certain number of selected firms in manufacturing industry. TheAltman Z-Score is used to estimate a firm's financial difficulties. The Z-Score value shows whether thefinancial position of the firm is good, moderate or risky. In this study, KNN and Naive Bayes algorithmsare used as classification methods. The Z-Score values of all firms are calculated and a certain numberof data for all three types are selected and taught to the system as learning data. Algorithms are run onthe financial parameters in the Z-Score formulas of companies not taught to the system. Over all data,The KNN and Naive Bayes algorithms achieve 84–88% and 75–86% success, respectively. This study,where data mining techniques are applied on a finance model and successful results are achieved, willcontribute to the application of different technologies in many different analysis processes of thefinancial sector.